Data Scientist Jobs in the UAE

About the Role Explore data, engineer features, and build machine learning models for real business challenges. Design, run, and evaluate experiments to support products such as fraud detection, recommendation engines, ranking, and personalisation. Collaborate closely with ML engineers and backend developers to bring successful models into production. Present insights and findings to both technical and non-technical stakeholders. Contribute to a collaborative, data-driven environment focused on continuous learning and innovation.Requirements 0–2 years of experience in Data Science (internships, research projects, and academic work are welcomed). Strong Python skills with experience using pandas, NumPy, and scikit-learn. Solid understanding of machine learning, statistics, and experimental design. Good SQL skills. Strong analytical thinking and communication skills. Nice to have: Exposure to Spark, Databricks, recommendation systems, fraud detection, or SaaS/high-scale product environments.Benefits Competitive salary with annual performance bonus. Comprehensive medical insurance. Annual flight allowance. Visa sponsorship. Annual leave entitlement. Learning and conference budget to support your professional growth. Hybrid working model with flexibility. Opportunity to work alongside experienced engineers and data scientists on cutting-edge AI/ML products with a distributed team across Dubai and Europe.

The Story So Far: We’re Building a Global Brand in Real EstateHuspy is one of the leading property technology companies in EMEA.Launched in 2020, we now operate in multiple cities across the UAE and Spain, expanding into Saudi Arabia and 3 more European markets by 2026.Today, we own the largest portion of the UAE mortgage market and are one of the fastest-growing players in every European city we’ve entered.We’ve raised over $140 million (Series A and Series B) from the world’s top investors, including Sequoia Capital, Founders Fund and Balderton Capital, to reshape the homebuying journey through powerful technology and agent-first tools.We’ve built a SuperApp that empowers real estate agents and mortgage brokers, bringing cutting‑edge technology to one of the world’s most traditional industries. We’re transforming how property transactions happen — faster, smarter, and better for everyone.We’re not slowing down.The question is: will you be part of what’s next?The Main Event: What You’ll Drive, Build, and OwnReal Estate Market Modeling: Build models applied to challenges such as valuation/pricing leveraging techniques from classic supervised ML to more advanced approaches.Multimodal Embeddings: Create vector representations of Real Estate entities, such as listings, combining images, text, and structured attributes to power search, matching, deduping, or recommendations.Data Analysis & Experimentation: Use SQL/Python to extract, clean, and analyze data; design experiments and evaluate model-product impact with robust metrics.Model Operationalization: Ship models to production with capabilities such as monitoring, automated rollout, or CI/CD (in partnership with engineering).Cross-functional Delivery: Partner with product, engineering, and operations teams to translate business problems into scalable ML solutions.The Perfect Match: What It Takes to Succeed at HuspyProven Experience: 4–8 years in applied data science/ML, delivering models that move real-world KPIs.SQL & Python Mastery: Strong in frameworks such as Pandas/NumPy/Scikit-learn...building reliable data pipelines, model training and evaluation.MLOps Fundamentals: Experience deploying/maintaining models (batch or real-time), versioning, CI/CD basics, observability, and reproducible training.Communication & Ownership: Clear with technical/non-technical stakeholders; can scope, prioritize, and explain tradeoffs.Comfortable with uncertainty, data quality issues, leakage risks, and market dynamics (location, seasonality, inventory shifts).Nice to Have: Software engineering experience; multimodal/vision experience; voice AI (ASR/NLU) exposure.Academic Background: Bachelor’s in STEM (Master’s a plus).By submitting this application, I agree that my personal data will be collected, processed, and retained by the company solely for the purposes of managing and assessing my candidacy.

En Decide4AI buscamos un/a Senior Data Scientist con disponibilidad para trabajar presencialmente en Abu Dhabi hasta, al menos, principios de 2027.Formarás parte de un programa estratégico de Transformación Digital e Inteligencia Artificial para una de las compañías energéticas más importantes del mundo, trabajando junto a equipos internacionales en iniciativas con impacto global y visión a largo plazo.Buscamos una persona práctica, versátil y orientada a la ejecución, capaz de participar en todas las fases de una solución de Data Science.🚀 ¿Qué harás?👉 Trabajar directamente con stakeholders del cliente para entender retos de negocio y traducirlos en soluciones analíticas.👉 Diseñar y desarrollar soluciones de Data Science end-to-end, desde la exploración de datos hasta la puesta en producción.👉 Construir modelos de Machine Learning, pipelines de datos y soluciones analíticas escalables.👉 Participar en proyectos de Data Engineering, Machine Learning, Optimización e IA Generativa.👉 Colaborar con equipos multidisciplinares de Data Science, Ingeniería y Negocio.👉 Comunicar resultados e impacto a perfiles técnicos y ejecutivos (C-level).🤝 ¿Cómo trabajarás?Te integrarás en un equipo internacional de aproximadamente 15 profesionales trabajando desde las oficinas del cliente en Abu Dhabi.El trabajo es principalmente presencial, colaborando estrechamente con cliente y equipos técnicos en un entorno altamente dinámico, multicultural y orientado a resultados.Trabajarás sobre tecnologías y proyectos relacionados con Data Science, Data Engineering, Machine Learning, Optimización e Inteligencia Artificial, utilizando principalmente Python, tecnologías cloud y arquitecturas modernas de datos.🎯 ¿Qué buscamos?✅ Nivel de inglés equivalente a C2 (imprescindible).✅ Disponibilidad para trabajar presencialmente en Abu Dhabi.✅ Experiencia sólida desarrollando soluciones de Data Science en entornos reales de negocio.✅ Experiencia trabajando directamente con clientes o stakeholders.✅ Excelente capacidad de comunicación y resolución de problemas.✅ Dominio de Python, Machine Learning y procesamiento de datos.✅ Experiencia con plataformas cloud (Azure, AWS o GCP).✅ Capacidad para combinar análisis, desarrollo, modelado y puesta en producción de soluciones.✅ Curiosidad, iniciativa, capacidad de adaptación, capacidad de aprendizaje rápido y orientación a resultados.✅ Comodidad trabajando en entornos ambiguos, dinámicos y altamente colaborativos.🌍 ¿Qué ofrecemos?✨ Participar en uno de los programas de Transformación Digital e IA más ambiciosos de Oriente Medio.✨ Contrato Indefinido.✨ Modelo presencial en Abu Dhabi desde las oficinas del cliente. Opción teletrabajo un día a la semana.✨ Alojamiento en hotel de cinco estrellas durante toda la estancia.✨ 100 € diarios para manutención.✨ Cuenta corporativa de Uber y tarjeta de gastos.✨ Un vuelo de ida y vuelta a España cada 4-6 semanas (o vuelo equivalente para tu pareja a Abu Dhabi).✨ Bonus mensual de desplazamiento de 1.500 €.✨ Seguro médico internacional premium.✨ Posibilidad de extensión del proyecto hasta agosto de 2027.✨ 500€ anuales en formación, asignados explícitamente a necesidades formativas del empleado.✨ Tarjeta regalo de 100€ de Amazon en Navidad.✨ 23 días de vacaciones al año.

Senior Data Scientist – AI Research LabWe are building the next generation of artificial intelligence systems, bringing together researchers, engineers and product teams to solve complex real-world problems using state-of-the-art machine learning. Our work spans large language models (LLMs), multimodal AI, agentic systems, reinforcement learning, computer vision and advanced predictive modelling.This is an opportunity to work in a research-led environment where experimentation, innovation and scientific thinking are valued as highly as engineering excellence.The RoleWe are looking for an exceptional Data Scientist to transform large, complex datasets into insights, models and algorithms that power cutting-edge AI products and research initiatives.You'll work alongside AI Researchers, Machine Learning Engineers and Software Engineers to develop novel approaches, evaluate model performance and build intelligent systems that solve meaningful business and scientific challenges.This role suits someone who enjoys working at the intersection of statistics, machine learning and applied AI.ResponsibilitiesDesign, build and deploy advanced statistical and machine learning models.Analyse large-scale structured and unstructured datasets to uncover meaningful insights.Develop predictive models using classical ML techniques and modern deep learning approaches.Partner with AI Researchers to evaluate foundation models, LLMs and multimodal systems.Build data pipelines, feature engineering frameworks and model evaluation methodologies.Design experiments and A/B testing frameworks to validate model improvements.Develop explainability, bias detection and model monitoring capabilities.Evaluate new research papers and translate academic advancements into production-ready solutions.Work with cloud-native data platforms and distributed computing environments.Present technical findings to both technical and executive stakeholders.Required ExperienceBachelor's, Master's or PhD in Computer Science, Data Science, Mathematics, Statistics, Artificial Intelligence or a related discipline.5+ years of commercial experience in Data Science or Machine Learning.Strong mathematical foundation including probability, statistics and optimisation.Expert Python programming skills.Experience with SQL and large-scale data processing.Strong experience with Scikit-learn, Pandas, NumPy and modern ML frameworks.Experience working with PyTorch or TensorFlow.Knowledge of feature engineering, model selection and hyperparameter optimisation.Experience deploying models into production environments.Strong understanding of evaluation metrics, experimentation and statistical significance.Excellent communication and problem-solving skills.Desirable ExperienceExperience working with Large Language Models (GPT, Llama, Claude, Mistral or similar).Knowledge of Retrieval-Augmented Generation (RAG).Experience with reinforcement learning or agentic AI systems.Familiarity with vector databases and embedding models.Experience with distributed computing (Spark, Ray or Dask).Knowledge of MLOps tools including MLflow, Kubeflow or SageMaker.Experience using Kubernetes and Docker.Exposure to computer vision, speech or multimodal AI.Publications, patents or open-source contributions within AI or machine learning.40/50k AED per month

Detailed Job Description : Data ScientistROLE PROFILE • Designs and develops scalable machine learning models and AI-driven solutions to address complex business challenges and enhance decision-making processesKEY RESPONSIBILITIES• Work with large and complex data sets to solve challenging business problems• Collect, clean, and preprocess large datasets for analysis & model training• Perform exploratory data analysis (EDA) to uncover insights and inform model development• Develop, train, and optimize machine learning models using state-of-the-art algorithms and frameworks• Build end-to-end ML pipelines , including data ingestion, transformation, model training, validation, and deployment• Automate workflows for model training, testing, and deployment using CI/CD pipelines and MLOps tools• Collaborate with cross-functional teams to integrate models into applications and deliver end-to-end solutions PROFESSIONAL EXPERIENCE/QUALIFICATIONS • 5 years of experience in data science, machine learning, or AI• Expertise in supervised/unsupervised learning , deep learning, NLP, computer vision, or generative AI (e.g., LLMs).• Strong proficiency in Python and/or R ; familiarity with SQL for data querying• Ability to build data pipelines (Spark, Airflow, Hadoop) and work with big data tools• Understanding of model serving , API development (FastAPI, Flask), and optimizing model performance for real-time or batch inference.• Knowledge of Docker, Kubernetes, CI/CD pipelines , and tools like MLflow/Kubeflow for model lifecycle management (MLOps)• Experience deploying models on AWS, Google Cloud, Azure, or similar (e.g., Sagemaker, Vertex AI)• Educational qualifications: Master in Computer Science or a related field.

About the CompanyLiquidity is the world's leading AI-powered private credit firm, pioneering a new standard in growth capital through a nexus of the sharpest minds in private credit and technology. With a global reach and regional expertise in every key market across North America, Europe, APAC and MENA, Liquidity supports visionary growth and mid-market companies in 45+ sectors, deploying multi-billion-dollar capital with unmatched speed, precision and adaptability. Powered by breakthrough decision science technology that deploys growth capital faster than any firm in capital markets history, Liquidity clears the path for innovative companies to move further, faster and at scale. Built on trust, Liquidity is backed by leading financial institutions including MUFG Bank Ltd., Spark Capital and KeyBank.About the RoleWe are looking for a Senior Data Scientist to research, architect, and deploy machine learning models and production-ready AI systems at the heart of Liquidity's credit intelligence platform. You will own the full lifecycle of data science solutions, spanning credit scoring, cash flow forecasting, and autonomous capital allocation workflows, directly shaping how we evaluate creditworthiness and deploy capital across a global portfolio. Beyond modeling, you will translate complex outputs into clear insights and present findings to credit, treasury, and investment stakeholders, closing the loop between algorithmic precision and real business decisions. This role is for highly quantitative problem-solvers who balance innovation with pragmatism, build iteratively from MVPs, and stay genuinely curious about how emerging tools can sharpen their work. You care about reliability, interpretability, and measurable impact, not just model performance in isolation.ResponsibilitiesCredit Intelligence & Predictive Modeling: Build and deploy models for credit scoring, cash flow forecasting, risk classification, and portfolio optimization that directly inform underwriting and lending decisions.Intelligent Workflows: Design data-driven agents with financial guardrails and human-in-the-loop controls for critical treasury and capital allocation decisions.Orchestration & Multi-Agent Systems: Coordinate complex, multi-step workflows using LLM pipelines and orchestration frameworks to analyze market data, liquidity constraints, and portfolio signals.Data Storytelling & Dashboarding: Translate model outputs and portfolio insights into clear, actionable dashboards and reports for credit and executive stakeholders.MLOps & Model Lifecycle: Manage the full model lifecycle, including experiment tracking, versioning, deployment, and monitoring, to detect drift, ensure reproducibility, and maintain production reliability.Production Engineering: Develop model-serving APIs and deploy within event-driven cloud architectures, collaborating with engineering on scalable, well-observed systems. Qualifications6+ years of experience in Data Science, Quantitative Modeling, or AI/ML, including 2–4 years deploying production-grade ML models, agentic AI, or LLM pipelines.Modeling: Time-series forecasting, credit scoring, regression, classification, and optimization; proficiency with tree-based models (XGBoost, LightGBM) and model interpretability techniques such as SHAP.Technical Stack: Advanced Python (Pandas, Scikit-learn); MLOps tooling (MLflow); exposure to deep learning frameworks (PyTorch or TensorFlow) a plus.Data & Databases: Strong SQL; experience with Postgres, MySQL, or Databricks.Visualization: Fluency in at least one dashboarding tool (Streamlit, Tableau, or Power BI).AI Fluency: Stays current with the rapidly evolving AI landscape; able to translate business problems into clear AI directives and effectively supervise and evaluate intelligent workflows.Software Engineering: Strong coding practices, with the ability to write clean, maintainable Python and debug complex issues across data pipelines, model serving, and integrated systems.Communication & Presentation: Able to distill complex quantitative work into clear narratives and present findings confidently to credit, investment, and executive stakeholders. Preferred SkillsMaster's degree or Ph.D. in a quantitative field (Computer Science, Statistics, Mathematics, Finance, etc.).Domain experience in FinTech, private credit, or quantitative finance.Infrastructure & deployment: Docker, CI/CD pipelines, cloud platforms (AWS Lambda, Serverless, Containers), and observability tooling (Langfuse, CloudWatch, or Datadog).NoSQL and alternative data stores: MongoDB, Neo4j, and vector databases.Familiarity with web technologies (REST APIs, basic HTML/JS) and ETL pipeline design.Experience with FastMCP or MCP-based tooling. Pay range and compensation package[Pay range or salary or compensation]Equal Opportunity Statement[Include a statement on commitment to diversity and inclusivity.]

Headquartered in Abu Dhabi, United Arab Emirates, specializes in developing AI-driven intelligent systems for defense and industrial sectors by integrating engineering and supply chain intelligence. The company focuses on transforming unstructured data—such as military standards and regulatory texts—into actionable insights through advanced AI models like generative AI, NLP, and predictive analytics, ensuring accuracy and reliability. Their solutions support high-stakes decision making, compliance automation, and risk forecasting to bolster critical operations and secure supply chain resilience.Job SummaryWe are seeking a Senior Data Scientist to lead the technical development and deployment of high-impact AI initiatives for advanced defense capabilities. In this pivotal role, you will transition from exploratory modeling to building production-grade AI systems that directly enhance the design, manufacturing, and procurement processes. You will serve as the technical liaison between unstructured data sources—such as regulatory texts and technical documentation—and structured engineering systems, including BIM/IFC models and SAP S/4HANA. Working within a structured delivery framework from Sprint Zero to Stage Gate, you will design and deploy AI engines that power two critical programs: the platform, which accelerates the systems engineering lifecycle, and Intelligent Supply Chain, which delivers predictive spend and risk analytics. Your expertise will drive innovation at the intersection of generative AI, predictive modeling, and system integration, ensuring compliance, efficiency, and resilience in high-stakes defense applications.Key ResponsibilitiesLead the development and deployment of generative AI and NLP solutions for engineering applications within the platform, including data exploration and analysis of large domain-specific datasets from both structured and unstructured sources to identify patterns and ensure data quality standards are met.Design, fine-tune, and deploy Large Language Models (LLMs) to interpret complex regulatory texts such as building codes and military standards, extracting structured rules for automated compliance checking and validation.Convert interpreted regulatory content into computer-processable formats (e.g., object-property-condition-value tuples) to enable execution by downstream compliance engines and systems.Architect NLP-driven methods to map natural language requirements directly to metadata entities across various schemas (e.g., linking 'systems design' to specific attributes in engineering models).Implement Retrieval-Augmented Generation (RAG) pipelines to enable high-accuracy querying of technical documentation and historical project data while minimizing hallucination risks in generated outputs.Develop time-series forecasting models to predict spend categories and material demand by integrating internal ERP data with external macroeconomic signals for supply chain optimization.Build machine learning classifiers to categorize supplier risks and operational anomalies, integrating diverse data sources to generate dynamic risk scores and operational insights.Design and oversee robust data extraction pipelines to transform raw data from Data Lakehouse environments, external web sources, SAP databases, and other systems into actionable features for predictive modeling and automated rule validation.Collaborate with backend engineers to integrate AI models into cohesive compliance and risk engines, ensuring seamless programmatic invocation via well-documented APIs.Optimize model performance to handle large-scale datasets and high-volume processing (e.g., analyzing thousands of supplier records) within operational timeframes, leveraging batching or asynchronous processing where necessary.Validate model outputs against test cases and historical data, debugging false positives/negatives to refine algorithms and ensure defense-grade reliability and accuracy in all applications.Qualifications And Requirements5+ years of experience in Data Science or Machine Learning, with a proven track record of deploying models into production environments.Expert proficiency in Python and standard ML libraries, including TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.Deep experience with transformer-based models (GPT, BERT, Llama) and prompt engineering techniques such as few-shot learning and fine-tuning for domain-specific tasks.Strong grasp of both supervised and unsupervised learning techniques.Proficiency in handling complex data structures (JSON, XML) and familiarity with database querying (SQL/NoSQL) or graph data structures.Experience with data extraction from specialized formats, including structured and unstructured sources.Understanding of how to expose models via RESTful APIs (Flask/FastAPI) and integrate them into larger software architectures.Solid understanding of statistics, probability distributions, and A/B testing, with the ability to identify and mitigate biases in datasets.Ability to quickly grasp complex domain terminology (e.g., construction regulations, defense standards, supply chain taxonomies) and translate them into logical workflows.Experience working in structured delivery models such as Agile or Sprint-based frameworks while adhering to rigorous validation and verification standards.Strong communication skills to collaborate effectively with Domain Experts, Backend Engineers, and Product Managers, aligning model outputs with real-world business logic.Technical SkillsExpert proficiency in Python and standard machine learning libraries, including TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy, with a strong grasp of both supervised and unsupervised learning techniques.Deep experience with transformer-based large language models (GPT, BERT, Llama) and advanced prompt engineering techniques, such as few-shot learning and fine-tuning, tailored for domain-specific applications.Proficiency in handling complex data structures (JSON, XML) and querying databases using SQL/NoSQL, with experience extracting data from specialized formats and graph data structures.Understanding of backend systems and the ability to expose AI models via RESTful APIs using frameworks like Flask or FastAPI, integrating them into larger software architectures.Solid foundation in statistics, probability distributions, and A/B testing, with expertise in identifying and mitigating biases in datasets.Experience designing and implementing Retrieval-Augmented Generation (RAG) pipelines to enhance accuracy and reduce hallucination in technical documentation and historical project data retrieval.Familiarity with data extraction pipelines to transform raw data from sources such as Data Lakehouse, external web platforms, SAP databases, and other structured/unstructured repositories into actionable features for predictive modeling and automated rule validation.Knowledge of model orchestration and optimization techniques to ensure high-performance execution, including batching, asynchronous processing, and integration with compliance or risk engines via robust APIs.Ability to validate model outputs against test cases and historical data, debugging false positives/negatives to achieve defense-grade reliability and accuracy.Company And Project FocusJoin a dynamic organization where innovation and data-driven decision-making are at the core of our mission. In this role, you will contribute to high-impact projects focused on leveraging advanced analytics, machine learning, and statistical modeling to solve complex business challenges. The team operates at the intersection of technology and strategy, delivering scalable solutions that enhance operational efficiency, optimize performance, and drive growth. Your work will directly support initiatives aimed at transforming raw data into actionable insights, ensuring alignment with both short-term objectives and long-term organizational goals.Location and Work EnvironmentPrimary Location: Abu Dhabi, United Arab EmiratesCompany: Sister Company of [the client]Project Focus: The platform and Intelligent Supply Chain initiativesWork Setting: Hybrid or on-site collaboration with cross-functional teams, including Data Engineers, Backend Engineers, and Domain Experts.Delivery Model: Structured 'Sprint Zero' to 'Stage Gate' framework, ensuring rigorous validation and iterative deployment of AI-driven solutions.Why Join This Role?This role is more than just model development—it is about shaping the intelligent systems that will define the industrial foundation of tomorrow. You will tackle real-world, high-impact challenges, from safeguarding product design and manufacturing against safety and compliance risks to anticipating supply chain disruptions that could threaten national security. By joining our team, you will transform raw data into actionable insights, giving organizations a decisive edge in decision-making and strategic foresight.

Lead Data Scientist – AI Lab | FintechLocation: Abu Dhabi My client is looking for a Lead Data Scientist to join a newly established AI Lab. This is a high-impact opportunity for a technically strong, hands-on Data Scientist who can take AI and machine learning solutions from concept through to production.The ideal candidate will have a strong Computer Science / technical academic background and be a genuine full-stack Data Scientist- someone who can write production-ready code, build models, work across the engineering stack and deploy solutions independently, rather than relying on separate teams to operationalise their work.Key ResponsibilitiesLead the design, development and deployment of advanced AI and machine learning solutions across banking use cases.Own the full lifecycle from problem definition, data preparation and modelling through to deployment, monitoring and optimisation.Develop production-grade solutions using Python, SQL and modern ML/AI frameworks.Build and productionise GenAI, LLM, RAG, NLP and agentic AI solutions where relevant.Work closely with Data Engineers, Software Engineers and Product teams to take AI solutions into production.Develop robust ML pipelines, APIs, model-serving components and MLOps processes.Establish best practices around model deployment, testing, monitoring, reproducibility and responsible AI.Evaluate emerging AI technologies and identify opportunities to create tangible value for the bank.Mentor Data Scientists and contribute to the technical direction of the new AI Lab.Ideal Candidate8+ years' experience in Data Science, Machine Learning, AI Engineering or a related technical field.Bachelor's or Master's degree in Computer Science, AI, Machine Learning, Mathematics, Statistics, Engineering or another highly quantitative discipline.Strong hands-on Python development skills and excellent SQL.Proven track record of taking machine learning / AI models into production.Strong understanding of software engineering principles including Git, APIs, testing, CI/CD and containerisation.Experience with cloud platforms such as AWS, Azure or GCP.Experience with modern ML/AI technologies such as PyTorch, TensorFlow, Hugging Face, LLMs, RAG, vector databases and agentic AI is highly desirable.Banking, financial services or fintech experience would be advantageous.What Will Differentiate YouMy client is particularly interested in "full-stack" Data Scientists who are equally comfortable experimenting with models and engineering them into scalable production systems.Strong preference will be given to candidates with a rigorous Computer Science or technical background over candidates whose background is primarily business, commercial or MBA-focused.The successful candidate will be a builder -technically autonomous, hands-on and capable of taking an AI solution from an initial idea all the way through to production.*** Only successful candidates will be contacted ***

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.Job DescriptionAs the leading delivery company in the region, we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users.As a Sr. Data Scientist (AI & ML) on the global AI hub, your mission will be to design, build, and ship the machine learning and generative AI systems that power decisions across product and business. You will own a particular domain end to end, working closely with product and business managers as part of a talented team of data scientists and machine learning engineers. You will own the full ML lifecycle, from problem framing, data modeling, and feature engineering through model training, deployment, serving, and monitoring in production. Many of our initiatives will focus on leveraging Generative AI and LLMs for tasks such as data enrichment, smart content understanding, and automated decision-making to enhance user experiences and business operations at scale.ResponsibilitiesFraming ambiguous business problems as well-defined machine learning and data science problems, with clear, objective success criteria.Providing high-quality, impactful insights and data-driven recommendations through rigorous analysis and automated reporting to drive strategic organizational choices.Designing, building, and shipping end-to-end machine learning and generative AI systems in production — spanning data pipelines, feature engineering, model training, serving, and monitoring.Taking on engineering-heavy work end to end: architecting robust ML-based systems, writing clean and scalable production code, and training, deploying, and maintaining reliable ML models that solve real business problems at scale.Training, evaluating, and iterating on models — selecting the simplest, most appropriate algorithms and architectures to deliver measurable business value.Leveraging LLMs and generative AI for data enrichment, smart content understanding, and automated decision-making within production systems.Building and maintaining the data models, features, and pipelines that power model training and allow us to measure performance and its drivers for your area of focus.Designing, planning, and analyzing experiments (A/B and multivariate tests) to rigorously measure model and product impact.Developing deep familiarity with source data and its generating systems through documentation, collaboration with engineering teams, and systematic data profiling.Partnering with product and business teams to identify high-impact opportunities and translate them into ML solutions and actionable, data-driven recommendations.Mentoring other data scientists in their growth journeys.Elevating engineering and ML best practices — improving our ways of working, tooling, MLOps, and internal training programs.QualificationsTechnical ExperienceDeep expertise in machine learning, generative AI, deep learning, recommendation systems, NLP, pattern recognition, data mining.Deep hands-on knowledge of ML and GenAI frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch, Transformers, LLM fine-tuning).Strong software engineering fundamentals: excellent coding skills, a solid grasp of data structures and algorithms, and proven ability in both general system design and ML system design.Proven experience building, deploying, serving, and monitoring ML models in production, with a strong grasp of MLOps practices.Strong data and ML engineering skills, including building and orchestrating data and training pipelines (e.g. via Airflow) and robust feature engineering.Excellent SQL and competence with reproducible analysis and modeling in Python.Solid statistical foundations, including experiment design and analysis (A/B and multivariate) and inferential, causal, and predictive methods.Familiarity with data modeling and dimensional design.Strong command over the entire ML lifecycle, from problem formulation and data auditing through modeling, deployment, interpretation, and presentation.Familiarity with product data (impressions, events, etc.) and product health measurement (conversion, engagement, retention, etc.).Experience with LLMs and NLP-based solutions for data enrichment and smart automation is a plus.Familiarity with BigQuery and the Google Cloud Platform is a plus.QualificationsBachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.5+ years of experience across data science, machine learning engineering, and generative AI, including shipping ML models to production.Experience building ML systems in an online consumer product setting is a plus.A good problem solver with a 'figure it out' growth mindset.An excellent collaborator.An excellent communicator.A strong sense of ownership and accountability.A 'keep it simple' approach to #makeithappen.

Major FunctionsThe Senior Data Scientist is responsible for designing, developing, and deploying advanced Machine Learning (ML) solutions for industrial applications such as reliability solutions, predictive maintenance, and operational/production optimization. The role focuses on building scalable, production-grade ML models that deliver measurable business value within complex Oil and Gas environments.This position requires strong domain expertise in Oil & Gas or Manufacturing industries, with a deep understanding of operational processes, asset performance, and industrial data ecosystems. The candidate will collaborate closely with engineers, subject matter experts, and business stakeholders to explore, validate, interpret, and operationalize data-driven solutions. The role demands both independent project leadership and effective cross-functional teamwork.Essential FunctionsDesign, develop, and deploy Machine Learning algorithms for industrial use cases such as reliability monitoring and predictive maintenance.Develop supervised and unsupervised learning models including regression and classification techniquesApply strong mathematical principles (linear algebra, calculus, probability, statistics) to model development and optimization.Develop scalable ML solutions using distributed computing frameworks (e.g., MapReduce, streaming technologies).Leverage domain expertise in Oil & Gas or Manufacturing to design context-aware predictive and prescriptive modelsCollaborate with data engineers and subject matter experts to identify, validate, and interpret new data elementsTranslate operational and industrial requirements into analytical and ML-driven solutionsLead end-to-end data science initiatives from problem definition through deployment and monitoringDevelop rapid prototypes using Python, R, or JavaScript, with exposure to Java or Scala as a plusDesign and implement MLOps practices including CI/CD pipelines for ML models, automated testing, model versioning, containerisation, deployment automation, monitoring, and performance drift management.Ensure models are production-ready, robust, explainable, and aligned with operational constraintsCommunicate technical insights clearly to both technical and non-technical stakeholdersTechnical & Education Qualifications RequirementMinimum 10 years of hands-on experience in the design, develop, deploy and operate Machine Learning algorithms for industrial use cases such as reliability monitoring and predictive maintenanceMandatory experience in Oil & Gas or Manufacturing industry environmentsDemonstrated domain expertise in industrial operations, asset management, process optimization, or predictive maintenanceProven experience designing and deploying ML solutions in real-world industrial settingsExperience with scalable ML systems (e.g., MapReduce, streaming frameworks)Experience collaborating with cross-functional industrial stakeholders including engineers and subject matter expertsExperience using Python, R, or JavaScript; familiarity with Java or Scala is a plusExperience working within modern development environments and AI-assisted workflowsMS in Computer Science, Electrical Engineering, Statistics, Engineering, or equivalent quantitative fieldProven applied Machine Learning experience (regression, classification, supervised and unsupervised learning)Strong mathematical foundation in linear algebra, calculus, probability, and statistics

Job Requisition ID: 180008Established in the 1930s as a trading business, Al-Futtaim Group today is one of the most diversified and progressive, privately held regional businesses headquartered in Dubai, United A”rab Emirates. Structured into five operating divisions; automotive, financial services, real estate, retail and healthcare; employing more than 35,000 employees across more than 20 countries in the Middle East, Asia and Africa, Al-Futtaim Group partners with over 200 of the world's most admired and innovative brands. Al-Futtaim Group’s entrepreneurship and relentless customer focus enables the organisation to continue to grow and expand; responding to the changing needs of our customers within the societies in which we operate.By upholding our values of respect, excellence, collaboration and integrity; Al-Futtaim Group continues to enrich the lives and aspirations of our customers each and every day.Overview Of The Role:The Senior Data Scientist will lead the development of advanced machine learning models to optimize demand forecasting and pricing strategies, driving increased profitability and customer satisfaction. This role requires a high level of expertise in Generative AI, MLOps, and cross-functional collaboration to ensure the seamless integration of data-driven solutions within the business. Success in this role is measured by the accuracy and robustness of predictive models, the optimization of pricing strategies, and the overall enhancement of customer analytics.What You Will Do:Design, develop, and deploy demand forecasting models using traditional and machine learning techniques like ARIMA, XGBoost, and LSTM.Leverage Generative AI (GenAI) to enhance demand forecasting accuracy by simulating future demand scenarios and improving model predictions.Implement dynamic pricing models using advanced algorithms to optimize pricing strategies based on demand predictions, inventory levels, and competitor data.Analyze customer behavior by applying clustering algorithms and predicting customer lifetime value (CLV) with machine learning models to drive personalized pricing strategies.Monitor, evaluate, and fine-tune model performance using metrics such as MAE, RMSE, and Precision/Recall, continuously improving model accuracy and robustness.Apply MLOps practices, including version control, model deployment pipelines, and automated testing, to ensure seamless integration, monitoring, and scaling of models across environments.Collaborate with cross-functional teams, including marketing, product, and sales, to ensure alignment between forecasting models and business objectives.Deploy and scale forecasting and pricing models on Azure cloud platform, leveraging CI/CD pipelines and model monitoring tools for real-time performance tracking and proactive issue resolution.Required Skills To Be Successful:Advanced machine learning model development and optimization skills.Expertise in Generative AI techniques for demand forecasting.Proficiency in MLOps practices and model deployment pipelines.Strong communication and collaboration abilities with cross-functional teams.What Qualifies You For The Role:Master's degree in Statistics, Data Science, Machine Learning, Mathematics, Computer Science, or a related quantitative field.10+ years of experience in data science, with at least 5+ years focused on demand forecasting, price optimization, and customer analytics.Strong hands-on experience with ARIMA, XGBoost, LSTM, and OR models.Proficiency in Python, SQL, Databricks, and cloud platforms (Azure, GCP).We’re here to provide excellent service but a little help from you can ensure a five-star candidate experience from start to finish.Before you click “apply”: Please read the job description carefully to ensure you can confidently demonstrate why this opportunity is right for you and take the time to put together a well-crafted and personalised CV to further boost your visibility. Our global Talent Acquisition team members are all assigned to specific businesses to ensure that we make the best matches between talent and opportunities. We not only consider the requisite compatibility of skills and behaviours, but also how candidates align with our Values of Respect, Integrity, Collaboration, and Excellence.As part of our candidate experience promise, we also want to make ourselves available to you throughout the application process. We make every effort to review and respond to every application.

Job Requisition ID: 180608Established in the 1930s as a trading business, Al-Futtaim Group today is one of the most diversified and progressive, privately held regional businesses headquartered in Dubai, United Arab Emirates. Structured into five operating divisions; automotive, financial services, real estate, retail and healthcare; employing more than 35,000 employees across more than 20 countries in the Middle East, Asia and Africa, Al-Futtaim Group partners with over 200 of the world's most admired and innovative brands. Al-Futtaim Group’s entrepreneurship and relentless customer focus enables the organization to continue to grow and expand; responding to the changing needs of our customers within the societies in which we operate.By upholding our values of respect, excellence, collaboration and integrity; Al-Futtaim Group continues to enrich the lives and aspirations of our customers each and every dayUse Data Science to Predict, Improve, and Transform Healthcare OutcomesAl-Futtaim Health is seeking an experienced Healthcare Data Scientist – Machine Learning & Clinical Analytics to join our HealthHub Corporate Office in Dubai Festival City.This is a specialist data science role focused on predictive modelling, machine learning, clinical analytics, healthcare data integration, and AI-driven decision support across our growing healthcare network.Important: This is not a Data Analyst, BI Analyst, Reporting Analyst, Power BI Developer, or dashboard-only role.We are looking for a hands-on Data Scientist who has personally built, trained, tested, and evaluated predictive models using real healthcare datasets such as electronic health records, claims, pharmacy data, laboratory data, clinical activity data, or healthcare operational data.The purpose of this role is to move beyond reporting what has already happened and help HealthHub predict what may happen next, optimise patient pathways, improve clinical decision-making, and support better healthcare outcomes.About The RoleAs a Healthcare Data Scientist, you will design, develop, and evaluate machine learning models and advanced analytics solutions that support clinical, operational, financial, and strategic decision-making.You will work closely with clinical leadership, medical directors, operations teams, finance, IT, health informatics, and compliance stakeholders to transform complex healthcare data into predictive insights and practical healthcare solutions.The role requires a strong combination of healthcare domain knowledge, statistical modelling, machine learning, Python or R, advanced SQL, healthcare data standards, and responsible healthcare AI practices.Key ResponsibilitiesBuild, train, test, and evaluate predictive machine learning models for healthcare use cases.Develop models that support clinical risk prediction, patient outcomes, utilisation, readmission risk, claims analytics, revenue cycle optimisation, and care pathway improvement.Analyse and model healthcare datasets including EHR, clinical, claims, pharmacy, laboratory, patient activity, and healthcare operational data.Apply statistical and machine learning techniques such as logistic regression, survival analysis, classification, clustering, random forest, XGBoost, and other predictive modelling methods.Prepare analytical datasets using advanced SQL, including cohort building, joins, window functions, longitudinal patient data, feature engineering, and data quality checks.Work with healthcare data standards and coding systems such as ICD-10/11, CPT, SNOMED CT, LOINC, HL7, and FHIR.Support clinical decision support, predictive analytics, healthcare AI, and data governance initiatives.Collaborate with clinicians and operational stakeholders to translate data science outputs into practical healthcare workflows.Evaluate model performance using appropriate metrics such as AUC, precision, recall, F1 score, sensitivity, specificity, calibration, and explainability methods.Ensure healthcare data privacy, ethical AI use, and compliance with relevant healthcare data governance requirements.Essential RequirementsCurrently residing in the UAE.Bachelor’s Degree in Data Science, Computer Science, Statistics, Biostatistics, Biomedical Engineering, Health Informatics, or a related quantitative discipline.Minimum 2–5 Years’ Experience In Data Science.Minimum 2 years’ experience working with healthcare datasets, clinical analytics, health informatics, healthcare AI, health insurance data, or health-tech data.Proven hands-on experience building predictive models or machine learning solutions.Advanced Python or R experience for data science, machine learning, statistical modelling, feature engineering, and model evaluation.Advanced SQL experience for complex extraction, analytical dataset creation, cohort building, and healthcare data preparation.Experience working with healthcare datasets such as EHR, clinical, claims, pharmacy, laboratory, patient activity, or healthcare operational data.Understanding of healthcare coding or interoperability standards such as ICD-10/11, CPT, SNOMED CT, LOINC, HL7, or FHIR.Ability to communicate technical outputs clearly to clinical, operational, finance, and leadership stakeholders.Highly DesirableMaster’s Degree or PhD in Health Data Science, Biostatistics, Computational Biology, Data Science, or a related field.Experience with UAE healthcare data environments, DHA regulations, NABIDH, Malaffi, or healthcare data residency requirements.Experience working within a hospital, clinic network, healthcare group, health insurance provider, health-tech company, clinical analytics team, or health informatics environment.Experience with clinical decision support systems.Experience With SHAP, LIME, Or Other Model Explainability Methods.Experience with Power BI, Tableau, Plotly, or Dash to communicate data science outputs to leadership.Who This Role Is Not ForThis role is unlikely to be suitable if your experience is primarily focused on:Power BI dashboards only.KPI reporting only.Excel reporting.SQL extracts without modelling.Descriptive analytics only.Claims audit reporting only.General business intelligence without predictive modelling.Data analysis without machine learning or statistical model development.Candidates must be able to demonstrate hands-on experience building data science or machine learning models using healthcare datasets.Why Join Al-Futtaim Health?Work from HealthHub Corporate Office in Dubai Festival City.Opportunity to shape healthcare AI and predictive analytics across a growing healthcare network.Work with clinical, operational, finance, and leadership stakeholders.Exposure to healthcare datasets and real-world clinical decision-making.Opportunity to support patient outcomes, operational efficiency, and healthcare innovation.Competitive salary and benefits package.Career development within one of the UAE’s leading healthcare organisations.About Al-Futtaim HealthcareWe Hear Your Ambition.For over 90 years, the Al-Futtaim Group has been bringing the world’s leading brands of lifestyle watches, cars, home furnishings and fashion to the UAE. The Group has now introduced a whole new way of holistic healthcare through HealthHub Clinics by Al-Futtaim, its multi-speciality chain of more than 20 clinics in Dubai with over 25 specialties offering the right combination of advanced diagnostics, proven medical expertise and specialised services.What gives our clinics an edge is that as a part of the Al-Futtaim Group, you can expect world-class quality standards, with access to the best medical services and facilities within a healing environment. It’s a new way of healthcare that’s designed to meet a patient’s needs with a complete range of smart healthcare solutions. As testimony to this, only recently, we’ve earned a rare milestone of being the only primary healthcare network in the UAE to receive the Gold Seal by a reputed international body: Accreditation Canada.As trusted partners to health, we at HealthHub Clinics adopt evidence-based learning that enables us to listen to our patients more carefully. It helps us in treating the cause and not just the symptoms, while applying global best practices to ensure quality of care for every family member. Most of all, we adopt a patient-centric approach to healthcare that is reflected in the promise of our core belief: “We Hear You.”

Job PurposeAs a Senior Associate – Data Scientist, you will design, build, and productionize advanced analytics and AI solutions that drive measurable business value. You will work closely with Data Product Owners, Data Analysts, BI Developers, and Data Quality Specialists to translate complex business challenges into data-driven models and experiments. Leveraging Python, SQL, and modern ML frameworks, you will develop scalable machine learning solutions that are explainable, governed, and aligned with organizational priorities.Roles And ResponsibilitiesTranslate business problems into data science projects by defining clear hypotheses, success metrics, and validation methods.Explore, clean, and transform structured and unstructured data using Python and SQL to prepare high-quality datasets for modeling.Design, train, and evaluate machine learning models using appropriate algorithms and statistical techniques (e.g., regression, classification, clustering, NLP, forecasting).Collaborate with engineering and platform teams to productionize AI models through reproducible pipelines and CI/CD workflows.Apply model explainability, fairness, and interpretability techniques (e.g., SHAP, LIME, feature importance) to ensure transparency and accountability.Support AI governance activities, including Model Risk Management (MRM) processes, ensuring compliance and responsible use of AI.Conduct and analyze A/B tests or controlled experiments to assess model and feature performance.Work with Data Product Owners to define business outcomes, monitor model performance post-deployment, and ensure continued relevance.Collaborate with Data Quality Specialists to ensure input data meets quality, lineage, and governance standards.Communicate results effectively through visualizations, storytelling, and presentations tailored to technical and non-technical audiences.Related Years Of Experience5+ years of experience in data science, applied machine learning, or advanced analytics.Proven experience delivering models that have been deployed and integrated into business processes or digital products.Experience working in agile, cross-functional teams with Product Owners, Data Analysts, and Data Engineers.Technical And Interpersonal SkillsAdvanced proficiency in Python (pandas, NumPy, scikit-learn, XGBoost, LightGBM).Strong command of SQL for data extraction, transformation, and validation.Experience working in Databricks or equivalent data and ML platforms.Familiarity with deep learning frameworks (PyTorch, TensorFlow) and ML lifecycle tools (MLflow, Airflow, Docker, Kubernetes).Understanding of model explainability, ethics, fairness, and governance.Knowledge of AI governance processes and documentation standards, including Model Risk Management (MRM).Exposure to cloud platforms (Azure, Snowflake) and APIs for integrating AI models into applications.Familiarity with version control (Git/GitHub) and collaborative coding practices.Excellent communication skills to explain technical findings in clear business terms.Collaborative and curious, with a passion for continuous learning and innovation QUALIFICATION Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.Master’s degree or higher in Data Science, Machine Learning, or Applied Statistics is an advantage.We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

About the CompanyCareem is building the Everything App for the greater Middle East — making it easy to move around, order food and groceries, manage payments, and more. Our purpose is simple: to simplify and improve people’s lives and build an awesome organisation that inspires.Since 2012, Careem has enabled earnings for over 2.5 million Captains, simplified the lives of more than 70 million customers, and built a platform where the region’s best talent and entrepreneurs thrive. We operate in 70+ cities across 10 countries, from Morocco to Pakistan.We’re now entering our next chapter — one powered by AI. We’re looking for AI talent: curious problem-solvers who know how to apply AI to build tools, automate workflows, and create real impact. Whether it’s streamlining operations, enhancing customer experience, or reimagining internal systems — we want people who can make Careem work smarter and move faster.About The TeamThe Personalization team sits within Careem's Data Science organization and owns the AI systems that decide what every user sees, in what order, and why across Food, Quik, and Shops. Our mission is to build the hyper-personalization layer for the Careem app: real-time, cross-vertical recommendation and ranking systems that learn from a user's behavior in one vertical and apply that understanding everywhere else they engage with Careem. As one of the senior technical leads on this team, you'll help define how Careem thinks about personalization at a regional scale working alongside the region's top data science talent, and pushing the state of the art using graph-based retrieval, transformer architectures, and real-time learning.What You'll DoOwn hyper-personalization use cases across Food, Quik, and Shops designing systems that learn a user's intent and preferences in real time and transfer that signal across verticals, so a user's behavior on one product makes every other product smarter.Be a technical lead on Careem's exploration of graph-based retrieval methods for recommendations including evaluating and building knowledge graph pipelines that power candidate generation and ranking at scale.Design and evaluate transformer-based architectures (XFY) for sequential and contextual recommendation moving Careem's ranking and retrieval stack beyond classical ML toward deep, attention-based models.Push toward online/streaming learning systems that adapt to user behavior within a session, not just from batch-trained models refreshed on a daily cadence.Identify where personalization signals, models, or infrastructure can be shared across Food, Quik, and Shops rather than rebuilt per vertical reducing duplicate work and compounding the value of every experiment.Be part of a 0-to-1 AI transformation for the Careem app from a personalization standpoint shaping how generative AI and LLM-based systems augment retrieval and ranking.Build a long-term vision for how Careem rethinks customer acquisition and engagement strategies, grounded in data-driven decision-making.Drive exploratory analysis to understand user behavior across verticals, identifying new levers to move metrics and building behavioral models that inform product enhancements.Shape and influence the ML models and instrumentation that optimize the product experience, surfacing new areas of opportunity and new product directions.Provide product leadership through data-driven recommendations communicating the state of the business, root-causing metric movements, and using experimentation results to influence product and business decisions.Implement scalable machine learning algorithms that run in production on large-scale data.Run exploratory data analysis to better understand user and business phenomena, and to discover untapped areas of growth and optimization.Answer complex analytical questions from large datasets to help shape Careem's products and services.Define and track key metrics for specific personalization initiatives.Design and run randomized controlled experiments (A/B tests), analyze results, and communicate findings to cross-functional teams.Continually challenge the status quo investigating new data processing technologies, retrieval architectures, and learning paradigms, and ensuring the team operates at industry-leading standards.Build and deploy retrieval-augmented generation (RAG) systems and other applications of large language models within the personalization stack.What You'll Need6-8 years of experience in data mining, predictive modeling, time series analysis, machine learning, and Big Data methodologies, including transformation and cleaning of structured and unstructured data.Advanced degree in a quantitative discipline such as Physics, Statistics, Mathematics, Engineering, or Computer Science.Solid experience with deep learning techniques including attention mechanisms, retrieval models, and transformer-based architectures (XFY or similar) applied to ranking or recommendation problems. Working with or evaluating knowledge graphs, graph neural networks, or graph-based retrieval systems is a strong plus. Careem is actively building toward graph-based retrieval for recommendations.2-4 years of industry experience in personalization, recommendation, or search is a MUST. Preferably gained in a product-driven company operating at scale.Strong problem-solving and coding skills.Solid knowledge of A/B testing methodology, classical ML, and deep learning.Solid understanding of recommendations, ranking, and retrieval systems end-to-end.Familiarity with or interest in online/streaming learning systems models that adapt within a session rather than relying solely on batch retraining, is a strong plus.Proficiency and demonstrated experience in Python, SQL, Spark, and Hive.Demonstrated experience with database technologies (e.g. Hadoop, BigQuery, Amazon EMR, Hive, Oracle, SAP, DB2, Teradata, MS SQL Server, MySQL).Demonstrated experience with business intelligence and visualization tools (Tableau, MicroStrategy, ChartIO, Qlik); geospatial data processing skills are a plus.What We'll Provide YouWe offer colleagues the opportunity to drive impact in the region while they learn and grow. As a full time Careem colleague, you will be able to:Work and learn from great minds by joining a community of inspiring colleagues.Put your passion to work in a purposeful organization dedicated to creating impact in a region with a lot of untapped potential.Explore new opportunities to learn and grow every day.Work remotely from any country in the world for 30 days a year with unlimited vacation days per year. Access to healthcare benefits and fitness reimbursements for health activities including gym, health club, and training classes.

About RevolutPeople deserve more from their money. More visibility, more control, and more freedom. Since 2015, Revolut has been on a mission to deliver just that. Our powerhouse of products — including spending, saving, investing, exchanging, travelling, and more — help our 75+ million customers get more from their money every day.As we continue our lightning-fast growth,‌ 2 things are essential to our success: our people and our culture. In recognition of our outstanding employee experience, we've been certified as a Great Place to Work™. So far, we have 13,000+ people working around the world, from our offices and remotely, to help us achieve our mission. And we're looking for more brilliant people. People who love building great products, redefining success, and turning the complexity of a chaotic world into the simplicity of a beautiful solution.About The RoleOur Data Science team solves complex problems with smart, practical solutions and improves how customers experience Revolut. Our Deep Learning Engineers are at the forefront of GenAI and LLM integration, building transformative products that range from user-facing tools to advanced process optimisation.We're looking for a Deep Learning Engineer to work with the most advanced LLMs available, developing solutions that have a tangible impact on millions of customers worldwide.You'll collaborate cross-functionally with Product Owners, Software Engineers, Data Analysts, and Operations Managers to deliver automated, scalable solutions that elevate and revolutionise customer interaction.Up to break barriers and shape what's next for the future of Revolut’s AI-driven capabilities? Let's get in touch.What You’ll Be DoingBuilding AI-driven features from scratch, like personal assistants, chatbots, copilots, and moreDeveloping user-focused and backend features using deep learningDelivering impactful, scalable, data-driven AI solutionsCollaborating with Product, Engineering, and Data teams to solve deep learning challengesIntegrating cutting-edge AI technologies to drive innovation at RevolutWhat You'll NeedExperience in deep learning within natural language processing area and large language modelsA bachelor's degree in a STEM major (mathematics, computer science, engineering)Excellent knowledge of data science (Python, SQL) and production toolsA deep understanding of probability and statistics fundamentalsBig-picture thinking to correctly diagnose problems and productionise researchExcellent communication and collaboration skills to partner with Product Owners and business headsNice to haveA master's or PhD in a quantitative disciplineSolid experience with additional programming languages, such as Java, Scala, C++Experience at a large tech company worth >$15BSchool/university Olympic medal competitions in physics, maths, economics, or programmingBuilding a global financial super app isn’t enough. Our Revoluters are a priority, and that’s why in 2021 we launched our inaugural D&I Framework, designed to help us thrive and grow everyday. We're not just doing this because it's the right thing to do. We’re doing it because we know that seeking out diverse talent and creating an inclusive workplace is the way to create exceptional, innovative products and services for our customers. That’s why we encourage applications from people with diverse backgrounds and experiences to join this multicultural, hard-working team.Important notice for candidates:Job scams are on the rise. Please keep these guidelines in mind when applying for any open roles. Only apply through official Revolut channels. We don’t use any third-party services or platforms for our recruitment. Always double-check the emails you receive. Make sure all communications are being done through official Revolut emails, with an @revolut.com domain.We won't ask for payment or personal financial information during the hiring process. If anyone does ask you for this, it’s a scam. Report it immediately.By submitting this application, I confirm that all the information given by me in this application for employment and any additional documents attached hereto are true to the best of my knowledge and that I have not wilfully suppressed any material fact. I confirm I have disclosed if applicable any previous employment with Revolut. I accept that if any of the information given by me in this application is in any way false or incorrect, my application may be rejected, any offer of employment may be withdrawn or my employment with Revolut may be terminated summarily or I may be dismissed. By submitting this application, I agree that my personal data will be processed in accordance with Revolut's Candidate Privacy Notice

Hyderabad, India / Dubai, UAEFull-timeApply to JobAbout The RoleWe are looking for a highly motivated Machine Learning Engineer / Data Scientist to join our dynamic team. In this mid-level role, you will leverage your expertise in data science and machine learning to design, build, and deploy innovative models and solutions that address real-world challenges.You will collaborate with cross-functional teams, including data engineers, product managers, and software developers, to turn complex datasets into actionable insights and build machine learning solutions that drive business value. This is a fantastic opportunity to work on impactful projects, expand your skill set, and contribute to cutting-edge advancements in AI and data science.Key ResponsibilitiesModel Development: Design, train, and evaluate machine learning models to solve business problems such as classification, regression, clustering, and recommendation.Data Preparation: Work with large and complex datasets, performing data cleaning, preprocessing, and feature engineering to optimize model performance.Model Deployment: Deploy machine learning models into production environments, ensuring scalability and robustness.Algorithm Selection: Research and implement state-of-the-art algorithms and methodologies to enhance model accuracy and efficiency.Collaboration: Collaborate with data engineering teams to build data pipelines and ensure efficient data flow for machine learning workflows.Visualization and Reporting: Create clear and actionable visualizations and reports to communicate findings and results to stakeholders.Monitoring and Maintenance: Monitor model performance in production, address drift or bias issues, and optimize models as needed.Tool Development: Build tools and frameworks to enable rapid experimentation and iteration of machine learning models.Documentation: Maintain comprehensive documentation for models, experiments, and processes.QualificationsEducation:Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field (or equivalent experience).Technical SkillsStrong programming skills in Python, R, or similar languages.Experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, or Keras.Proficiency in data manipulation and analysis using tools like Pandas, NumPy, and SQL.Experience with big data technologies such as Spark, Hadoop, or similar.Knowledge of cloud platforms and services (e.g., AWS SageMaker, Google AI Platform, Azure ML).Familiarity with MLOps practices and tools for CI/CD in machine learning workflows.Understanding of data visualization tools like Matplotlib, Seaborn, or Tableau.Strong grasp of statistical methods, probability, and optimization techniques.Experience3–5 years of experience in machine learning, data science, or a related field.Proven experience building and deploying machine learning models in production.Experience with natural language processing (NLP), computer vision, or time-series analysis is a plus.Soft SkillsStrong problem-solving and analytical thinking abilities.Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.Ability to work independently and collaboratively within a team.Curiosity and eagerness to stay updated on the latest advancements in machine learning and AI.About The CompanyDatamaze is a dynamic company specializing in AI, Data, and Analytics consulting services. We are dedicated to transforming businesses by leveraging the power of data and artificial intelligence. With a team of industry experts in technology, business strategy, and data science, Datamaze offers a range of services including data strategy development, AI model creation, advanced analytics, and data visualization. Our approach is client-centric, focusing on creating customized solutions that address unique business challenges and objectives. The team, comprising data scientists, AI experts, strategists, and engineers, is committed to continuous learning and innovation.Datamaze positions itself as a trusted partner for businesses looking to navigate the complex data and AI landscape, aiming to optimize operations, inform decision-making, and maintain a competitive edge.Apply Now

Job PurposeJoin the Emirates Group Analytics Centre of Excellence (ACoE), where data, AI and innovation power decisions across one of the world's most recognised aviation and travel brands.As a Data Scientist/AI Engineer, you will solve complex business challenges using machine learning, advanced analytics, GenAI and Agentic AI. Working across commercial, operational and customer domains, you will transform vast amounts of data into actionable insights, intelligent products and measurable business outcomes.This is an opportunity to work on real-world, large-scale problems while helping shape the future of AI and data-driven decision making at Emirates Group.In This Role, You WillDevelop and deploy machine learning, Agentic AI and analytics solutions that drive measurable business impact.Analyse large structured, semi-structured and unstructured datasets to uncover insights and opportunities.Build predictive, prescriptive and optimisation models to solve business challenges across the Emirates Group.Partner with stakeholders to translate complex business questions into scalable data science solutions.Create visualisations, dashboards and analytical tools that support decision-making.Contribute to the development of reusable libraries, frameworks and production-ready data science assets.Apply experimentation techniques including A/B testing, segmentation and customer analytics.Collaborate with engineers, analysts and product teams in an agile delivery environment.Support the development and deployment of AI-powered products and intelligent automation capabilities.QualificationTo be considered for this role, you must meet the below requirements:QualificationsMSc or PhD in Data Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, Operations Research, Computer Science, Economics or a related quantitative discipline.Experience2-4+ years of experience delivering advanced analytics, machine learning or AI solutions in a commercial environment.Knowledge & SkillsStrong hands-on experience across the modern Data Science ecosystem.Experience developing and deploying Machine Learning, GenAI, LLM and Agentic AI solutions.Experience with AI Engineering practices including model deployment, monitoring, evaluation, prompt and context engineering and scalable AI application development.Proficiency in Python, SQL and modern analytical toolsets.Experience with Sparkor distributed data processing technologies.Experience with Git, Docker, CI/CD and MLOps workflows.Experience building reusable libraries, APIs or production-grade data science solutions.Strong problem-solving mindset with the ability to communicate technical concepts to non-technical audiences.Experience delivering solutions in complex, fast-paced environments. Preferred ExperienceExperience building and deploying AI applications using LLM orchestration frameworks (LangGraph, LangChain, Semantic Kernel or equivalent).Experience with Retrieval Augmented Generation (RAG), vector databases, AI agents and multi-agent systems.Experience evaluating, monitoring and governing production AI systems.Understanding of cloud-native AI platforms and modern AI engineering best practices.Salary & benefitsJoin us in Dubai and enjoy an attractive tax-free salary, industry-leading travel benefits, and access to one of the most exciting AI and data environments in the region. Alongside discounted flights and hotel stays worldwide, you'll have the opportunity to work on high-impact projects at global scale while advancing your career with Emirates Group.

Job PurposeJoin the Emirates Group Analytics Centre of Excellence (ACoE) and help shape the future of data science, artificial intelligence and advanced analytics across one of the world's leading aviation and travel organisations.As a Senior Data Scientist/ Senior AI Engineer, you will lead the design and delivery of innovative machine learning, optimisation and AI solutions for business that influence strategic decisions, improve operational performance and create exceptional customer experiences. You will work on complex challenges at scale while mentoring others and driving the adoption of AI and advanced analytics across the organisation.In This Role, You WillLead end-to-end AI initiatives from problem definition through to deployment and value realisation.Partner with business leaders to transform strategic challenges into scalable AI and analytics solutions.Design and implement advanced machine learning, optimisation and simulation models.Develop AI-powered capabilities leveraging GenAI, LLMs and Agentic AI technologies.Drive experimentation, model validation and performance measurement to ensure business impact and automate business decisions. Lead the development of reusable data science frameworks, libraries and production-ready solutions.Collaborate closely with engineering teams to operationalise machine learning and AI products.Mentor and coach junior data scientists while helping shape best practices across the wider analytics community.Champion innovation and identify emerging technologies that can create competitive advantage.QualificationTo be considered for this role, you must meet the below requirements:QualificationsMSc or PhD in Data Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, Operations Research, Computer Science or a related quantitative discipline.Experience4-7+ years of experience delivering advanced analytics, machine learning, optimisation or AI solutions in large, complex organisations.Knowledge & SkillsExpert knowledge of machine learning, statistical modelling and advanced analytics.Strong experience with GenAI, LLMs, Agentic AI and emerging AI technologies.Hands-on AI Engineering experience including model deployment, Agentic orchestration frameworks, evaluation frameworks, observability and monitoring, RAG architectures and scalable AI application development.Experience with optimisation frameworks such as Gurobi, FICO or CPLEX.Strong programming skills in Python and SQL.Experience with Git, Docker, CI/CD pipelines and MLOps practices.Proven experience deploying production-grade analytics and AI solutions.Strong stakeholder management and communication skills with the ability to influence senior leaders.Experience mentoring and developing technical talent.A commercial mindset focused on delivering measurable business value through AI and analytics. Preferred ExperienceExperience building and deploying AI applications using LLM orchestration frameworks (LangGraph, LangChain, Semantic Kernel or equivalent).Experience with Retrieval Augmented Generation (RAG), vector databases, AI agents and multi-agent systems.Experience evaluating, monitoring and governing production AI systems.Understanding of cloud-native AI platforms and modern AI engineering best practices.Salary & benefitsJoin us in Dubai and enjoy an attractive tax-free salary alongside exceptional travel, healthcare and lifestyle benefits. You'll work on some of the most exciting AI, data science and optimisation challenges in the industry while helping shape the future of analytics at global scale.

Murphy AI deploys voice AI agents that help banks collect debt. We’ve built a fully-fledged platform designed to optimize recovery rates while maintaining respectful and personalized communication. Our advanced automation streamlines the process of collecting overdue invoices for banks and other industries, providing a seamless and effective solution.Our AI-powered agents adapt instantly, engaging with debtors across channels like voice, messengers, email and sms to maximize results while preserving trust. By combining advanced artificial intelligence with powerful automation, we’re setting a new standard for how businesses recover payments.As a fast-growing startup that has already made an impact within less than a year in the market, we are building a talented team to scale our operations and drive our vision forward 🌟About The RoleWe're looking for a Data Scientist to build the Murphy’s brain — the ML that decides who we contact, when, how and how often, to recover the most debt inside hard legal limits. Recovery is a data problem before it's a voice problem, and you own the data problem. This is one of the highest-leverage seats in the company: your models set the strategy every AI agent executes, on every call.Murphy builds AI voice agents that collect overdue debt for banks: more recovered, faster, cheaper, fully compliant, and respectful to the debtor. We're live with Santander, Revolut, BBVA and dozens others. We've proven the product in large-scale pilots with top-tier banks — now we're making every contact smarter, and we need a scientist to own the models that decide how we collect.What you'll doOwn the contact strategy. Who Murphy contacts, when, how often, on which channel — voice, WhatsApp, etc. — to maximise recovery inside hard legal guardrails.Model the debtor. Propensity and uplift models — who picks up, who pays, who responds to which voice, script or offer — turned into live segments the agents act on.Optimise with experiments. A/B tests and bandits over timing, cadence, voice and negotiation policy; find what lifts recovery, and ship it fast.Own business-level outcomes. Collaborate with product, engineering and commercial teams to define solutions and improve the key metrics.Who you areYou hold a degree in mathematics, statistics, machine learning, or computer science.Rigorous with probability and statistics. Experimental design, causal inference. You reach for the right tool, and you know when a result is real.AI-native, ruthless on quality. You reach for AI to automate and streamline by default — and you know exactly where it gets sloppy. You never let that through, and you control quality rigorously.You don’t need a collections or fintech background. We’d rather teach the domain to a killer than hire a lifer who can’t ship — you’ll pick up the domain, the data and the regulation cold, fast.Requirements2+ years shipping ML that ran in production and moved business metrics. Models that pick the best next action and measure whether it actually changed the outcome; ranking, pricing or contact-strategy models. Models that ship as code, not notebooks.Expert Python. Comfortable in a real production codebase — you take a model from idea to production and monitor it. We use Python for ML/AI services and TypeScript around it, on AWS and PostgreSQL.Statistics you can defend. Experimental design, causal inference, measuring the real effect of an action — not just correlations. You know when a result is real, when it’s noise, and how to test it.Experimentation. You’ve designed, run and interpreted A/B tests or bandits on live traffic, and shipped the winner.You turn models into decisions. You can explain to stakeholders why the model says to call this client at 6pm — and defend it.🤝 What we offer💰 Salary at the top of the benchmark.📈 Fair equity with enormous upside potential.🧩 Real Ownership - Murphy's strategy is yours to drive.🙌 Small team, high autonomy, and outsized impact.🗣️ The founding team's direct attention, and a category with a $300B+ industry behind it.🛜 Hybrid & Flexible: Our default setup is hybrid – 3 days a week at our office and 2 days of remote work.📚 Our Process1️⃣ First Interview – Getting to Know YouA conversation with a future teammate who’s excited to find a new colleague. We’ll talk about your story, what drives you, and what you’re looking for next—no trick questions, just a genuine exchange.2️⃣ Second Interview – Deep DiveYou’ll meet the Hiring Manager and potentially another team member. This is a more technical discussion where we explore your skills in detail, walk through real scenarios, and answer any questions you might have about the role.3️⃣ Tech Assessment or Business CaseA practical exercise to see how you approach challenges similar to those you’d tackle at Murphy. You’ll have time to reflect and showcase your thinking—no rush, no surprises.4️⃣ Call with the FoundersOur founders meet every team member and it’s a great opportunity for you to learn about the company and its direction.👉 To learn more about how we hire and what to expect at every step, feel free to explore our Hiring Guide!👉 We are committed to building a diverse, inclusive, and equitable workplace where everyone, regardless of background, identity, or experience, feels valued and empowered to thrive. We believe that different perspectives drive innovation and success, and we actively foster an environment where all voices are heard and respected.