Your AI career in the UAE starts here

We have partnered with a leading consumer-focused business in the UAE to hire a Data Scientist. This is a role for someone who is genuinely curious about why people buy what they buy. The business sits on a rich and growing pool of customer data, and this person will turn that data into a real understanding of buyer behaviour, intent and emerging trends. The insight you produce will shape commercial decisions at the highest level, so if you want your work to actually move the needle rather than sit in a dashboard nobody opens, this is worth a look.This role suits a data scientist with strong commercial instincts who can bridge the gap between rigorous modelling and decisions the business can act on.About the role:Build models that decode buyer mentality, purchase intent and behavioural trends, turning raw customer data into insight the business can act onDevelop predictive and segmentation models that anticipate customer behaviour, identify emerging patterns and inform commercial strategyWork closely with commercial, marketing and product teams to frame the right questions and deliver answers that drive real decisionsTranslate complex analysis into clear, compelling narratives that resonate with non-technical stakeholders and senior leadershipDesign and run experiments that test hypotheses about customer behaviour and measure the impact of commercial decisionsContribute to the evolution of the data science function, bringing new techniques, tools and thinking into the team About you:5 years of experience in data science, with a track record of building models that have influenced real business decisionsStrong proficiency in Python and SQL, with hands-on experience across the full modelling lifecycle from exploration to deploymentSolid grounding in machine learning techniques including classification, clustering, regression and forecastingExperience working with customer, behavioural or transactional data to understand and predict buyer behaviourCommercially minded, with the ability to connect analysis directly to revenue, retention and growth outcomesStrong communicator who can turn technical work into insight that non-technical stakeholders understand and trustFinancial services or retail experience is strongly preferred

We are looking for an experienced AI Development Engineer to join an exciting enterprise AI transformation project with a leading consulting organization.If you have hands-on experience building GenAI applications, RAG pipelines, AI agents and enterprise AI solutions, we would love to hear from you!Key Responsibilities:Develop GenAI applications, RAG pipelines, AI agents, copilots and automation workflows.Build responsive user interfaces using React, Next.js and TypeScript.Develop APIs, data connectors and AI integrations using Python and Azure AI services.Build PoCs, MVPs and reusable AI solutions for enterprise clients.Support AI testing, performance optimization, hallucination checks and responsible AI implementation.Required Skills & Experience:5–8 years of experience in software development, AI, cloud or automation.Strong hands-on experience with Python, FastAPI, React or Next.js.Experience with Azure OpenAI, Azure AI Foundry and Azure AI Search.Strong knowledge of RAG, embeddings, vector databases, prompt engineering and AI agents.Experience with APIs, Git, CI/CD, containers and automated testing.Good communication skills and experience working in Agile teams.All applications will be treated with strict confidentiality.

BUSINESS INTRODUCTIONMajid Al Futtaim Holding is the leading shopping mall, retail, communities, entertainment developer and operator in the Middle East, North Africa, and Central Asia regions. With over 43,000 people, revenues of over US$ 11 Billion, and operations in 18 countries. Some of the iconic brands we carry include Mall of the Emirates, Carrefour, All Saints, Lego, City Center, Abercrombie & Fitch, & Vox Cinemas. We believe in making Great Moments for Everyone, Every day.JOB TITLEData Science Manage | MAF LifeStyle | LifestyleROLE SUMMARYThis role is the primary owner of demand forecasting, demand sensing, demand planning, and advanced customer segmentation capabilities – driving measurable commercial impact across a multi-brand, multi-market retail portfolio spanning UAE, KSA, Kuwait, Qatar, and Bahrain. The role partners closely with brand owners, buying and planning teamsROLE PROFILEOwn end‑to‑end demand forecasting across SKU, category, and brand levels (short, medium, long term), incorporating seasonality, promotions, sell‑through, and external market factors across GCC markets.Lead demand sensing initiatives using real‑time POS, digital, and macro signals to anticipate near‑term demand shifts and enable rapid commercial decisions.Partner with Buying & Planning teams to translate forecasts into OTB, replenishment, markdown optimization, and NPI strategies, presented in clear commercial language.Design advanced customer segmentation models (RFM, CLV, behavioral and propensity models) to enable personalized marketing, CRM, and loyalty activation.Identify and priorities high‑impact AI use cases across pricing, assortment, promotions, churn, store clustering, and next‑best‑action with quantified business value.Drive adoption of Computer Vision solutions including footfall analytics, shelf compliance, planogram adherence, visual search, and automated product tagging.Lead NLP and conversational AI initiatives such as chatbots, sentiment analysis, multilingual (Arabic/English) text analytics, and automated product content generation.Build and scale production‑grade ML solutions on Azure/Microsoft Fabric, including automated pipelines, monitoring, drift detection, and executive reporting via Power BI.REQUIREMENTSBachelor’s degree in STEM (Science, Technology, Engineering, Mathematics).Advanced degree in related topics is a strong plus.Background or previous experience in retail, fashion, or lifestyle industry is strongly preferred.Experience in GCC/MENA markets is an advantage.Strong customer segmentation & CLV modeling experience.WHAT WE OFFERAt Majid Al Futtaim, we’re on a mission to create great moments, to spread happiness, to build, experiences that stay in our memories for a lifetime. We’re proud to say that over the past 27 years, we have built a reputation as a regional market leader in what we do. Join us!Work in a friendly environment, where everyone shares positive vibes and excited about our future.Work with over 45,000 diverse and talented colleagues, all guided by our Leadership Model.

AI Quantitative ResearcherWe are working with a leading quantitative trading firm based in Abu Dhabi to find an AI Researcher to join their team. Our client applies cutting edge AI research to financial markets, combining rigorous quantitative methods with the latest advances in machine learning.You will research and develop AI-driven quantitative trading strategies, exploring vast amounts of market and alternative data. You'll invent and apply state of the art technologies inspired by large language models, agentic AI agents, deep neural networks, transformers, and advanced prompt engineering to discover and capitalize on trading opportunities. You'll join a team of top AI talent recognized as leaders in their field, widely cited in top-tier journals, working in a collaborative, flat environment.What you'll bring:Master's or Ph.D. in a quantitative field (Computer Science, EE, Applied Math, Statistics, Quantitative Finance, Physics, or similar).Experience with statistical and ML/AI methods: classification, clustering, regression, optimization, signal processing, time-series analysis, Bayesian methods, neural networks, and related techniques.Deep knowledge of large language models, agentic AI agents, and deep neural networks (NLP, vision, speech, finance, etc.).Experience designing or deploying autonomous/multi-agent AI systems is a plus.Track record of impactful research, academic or professional.Strong programming skills (Python, C++, PyTorch, TensorFlow).What's on offer:Flat structure with direct executive exposure, work closely with leadership from day one.Top tier compensation, reflecting the caliber of talent on the team.State of the art systems and infrastructure to support cutting-edge AI research.The opportunity to work at the frontier of AI, applying LLMs, agentic systems, and deep learning to real world financial markets.

Role: Machine Learning EngineerLocation: Dubai Department: Technology & OperationsReports To: CTOPosition: Full-TimeAbout us:GlobalDrum is empowering the media sector to own, understand, and monetise their most valuable social audiences, using live audience behavioral data for brands to operate diversified business models on demand for themselves. We are evolving our unique next-generation B2B2C Platform as a Service (PaaS) that operates on a globally distributed cloud infrastructure incorporating a scalable, event-driven architecture using the latest AI and data techniques to evolve an entire sector.Located in London, Dubai, New York and Dubai, the Company is at the centre of reshaping how global brands will evolve in a sector valued at $276Bn in 2025 representing 30% of all digital ad spending. If this seems too ambitious for you, then don't apply. Job Description:We are looking for a visionary Machine Learning Engineer to become our first-ever ML hire, embedding data science and applied ML into the heart of our AI-native, multi-tenant platform. You will work directly with the Director of Engineering and product owners to turn audience, content, and revenue data into models that power recommendations, audience understanding, and monetisation decisions across the platform.This is a rare opportunity to define the ML function from the ground up: choosing the stack, setting the standards, and building the first production models that the rest of the engineering org will be built around.Key Responsibilities:Own Recommendations End-to-End: Design, build, and iterate on recommender systems that surface content and audience opportunities to our media partners.Build the ML Foundation: Establish the first ML pipelines, feature stores, experimentation frameworks, and model-serving infrastructure for the platform, since none currently exist.Data-to-Product Pipeline: Partner with the engineering team to design real-time, event-driven data pipelines that feed model training and low-latency inference.Experimentation & Evaluation: Define offline and online evaluation methodology (A/B testing, holdout sets, ranking metrics) to validate model impact on engagement and revenue.Set ML Standards: Establish best practices for model development, versioning, reproducibility, monitoring, and responsible use of data Stay Hands-On: Write production-grade ML code, heavily leveraging modern AI coding assistants and agentic development workflows to move fast as a team of one (initially).Cross-Functional Partnership: Work closely with the Engineering and platform/revenue product owners to translate business and product questions into ML-solvable problems.Scale the Function: As the first ML hire, help define the roadmap and hiring plan for the ML team as it grows.Required Skills and Qualifications:Proven, hands-on experience building and deploying recommender systems in production Working knowledge of graph-based learning, including Graph Neural Networks.Solid understanding of network science fundamentals.Experience designing and training models on large-scale, real-world data, including handling sparsity, and skewed engagement distributions.Comfortable owning the full ML lifecycle: feature engineering, training, evaluation, deployment, and monitoringFluency with modern ML tooling (e.g., PyTorch/TensorFlow and standard MLOps practices).Experience using AI coding assistants and agentic workflows to accelerate development.Track record of working effectively in an early-stage startup environment.Bonus Points If You Have...Exposure to the media and/or news technology ecosystem.Experience in AdTech: advertising networks, ad serving, audience segmentation.Preferred Experience/Qualifications:Strong domain knowledge in SaaS/PaaS, MarTech, or AdTech is highly valued.Experience building models that directly optimize platform revenue outcomes.Experience building recommendation systems in production using LLMs and VLMsComfortable being the sole ML voice in the room initially, while communicating clearly with engineering and product stakeholders who may not have deep ML backgroundWhy Join Us?The chance to build a ground-breaking AI platform from day oneCompetitive equity options package and salaryFlexible working environment

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Head Of Data Science & Credit Risk based in United Arab Emirates.As Head of Data Science & Credit Risk, you will lead the strategy behind ML-powered underwriting and credit risk decisioning across multiple fast-growing markets.You will own the full lifecycle of risk models, from development and deployment through monitoring, experimentation, and measurable business impact.The role combines deep technical leadership with responsibility for credit policies, portfolio performance, and responsible lending practices.You will build and mentor a high-performing team of data scientists and risk analysts while remaining actively involved in complex technical challenges.Working closely with Engineering, Product, Finance, and executive stakeholders, you will turn advanced analytics into practical decisions that support sustainable growth.You will help improve approval rates, automate decisioning, identify new customer segments, and strengthen portfolio health through data-driven strategies.This is a greenfield leadership opportunity in a mission-driven fintech environment focused on expanding fairer and more accessible financial services.AccountabilitiesML and model development: Lead the design, testing, deployment, and ongoing improvement of machine learning models for credit decisioning, fraud detection, risk segmentation, customer value, monetization, and marketing attribution.Underwriting innovation: Develop underwriting algorithms using alternative data sources to strengthen risk assessment while responsibly expanding access to financial services.Real-time decisioning: Build and scale real-time or near-real-time scoring models across multiple markets and products.Model governance: Ensure models are interpretable, robust, fair, and reliable, with appropriate monitoring for accuracy, feature stability, performance, and drift.MLOps: Establish strong practices for experimentation, model versioning, deployment, monitoring, and production lifecycle management.Credit risk strategy: Develop and manage credit risk frameworks, policies, approval strategies, risk thresholds, and customer segmentation approaches adapted to individual markets.Portfolio monitoring: Track portfolio and risk metrics, investigate material changes, and establish early-warning indicators for potential deterioration.Experimentation: Simulate policy and model changes, lead A/B testing, and use performance data and business KPIs to continuously refine decisioning strategies.Stress testing and provisioning: Lead stress testing and expected credit loss modeling while partnering with Finance on provisioning and capital allocation.Market expansion: Develop localized risk models and policies that support expansion into new markets while aligning with applicable regulatory requirements.Team leadership: Build, lead, coach, and mentor data scientists and risk analysts while remaining hands-on with technical problem-solving and model development.Strategic planning: Own the data science and credit risk roadmap, aligning priorities with business growth, product development, and market expansion objectives.Executive communication: Present model performance, portfolio trends, analytical insights, and strategic recommendations clearly to executive leadership and board-level stakeholders.Cross-functional partnership: Work closely with Engineering, Product, and Finance to translate analytical findings into measurable business outcomes.External partnerships: Evaluate and establish relationships with alternative data providers and credit bureaus.Business impact: Improve approval rates while maintaining target default rates and responsible lending standards, reduce time-to-decision, strengthen unit economics, and identify new customer and product opportunities.RequirementsProfessional experience: 10+ years of combined experience across data science, machine learning, and consumer credit risk, ideally within fintech, digital lending, BNPL, or earned wage access.Credit risk leadership: Proven experience developing and managing credit policies and portfolios at scale across multiple products, markets, or both.Production ML: Demonstrated success building, deploying, and monitoring production machine learning models within real-time or near-real-time decisioning environments.Experimentation: Strong hands-on experience with experimentation and A/B testing to assess the impact of model and policy changes.Statistical expertise: Strong mathematical and statistical foundations, combining classical statistical techniques with modern machine learning approaches.Data skills: Strong proficiency in SQL and exploratory data analysis, alongside practical experience working with cloud-based data platforms.Cloud technology: Experience with cloud data infrastructure is required; familiarity with GCP BigQuery is useful but experience with this specific platform is not mandatory.Technical leadership: Experience building and leading technical teams while remaining actively engaged in model development, analytical work, and complex problem-solving.Communication: Excellent communication skills, with the ability to explain sophisticated models, risk concepts, and analytical recommendations to non-technical stakeholders.Business judgment: Strong commercial understanding and the ability to connect technical and risk decisions with growth, portfolio performance, unit economics, and return on investment.Startup mindset: Adaptable, proactive, and comfortable operating in a fast-paced environment where priorities can evolve quickly.Regional expertise: Familiarity with Southeast Asian credit markets, credit bureaus, and alternative data sources is an advantage.MLOps tools: Experience with MLflow or similar frameworks for production machine learning development and deployment is a plus.Regulatory knowledge: Understanding of IFRS 9 and local credit regulations across multiple markets or regions is beneficial.BenefitsCompetitive compensation: Salary based on experience and location.Equity participation: Opportunity to participate in the company’s equity program.Leadership opportunity: Build and shape a growing data science and credit risk function from the ground up.Professional growth: Opportunities to expand your leadership, technical expertise, and strategic influence within a rapidly growing organization.Modern technology: Work with a modern machine learning stack and cloud-based data infrastructure.International scope: Lead data science and credit risk initiatives across multiple markets and support international expansion.Meaningful impact: Help develop models and financial services designed to expand responsible access to financial products for underbanked employees.Mission-driven environment: Contribute to improving financial well-being through fairer, more accessible financial services.How Jobgether WorksWe use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.We appreciate your interest and wish you the best! Why Apply Through Jobgether?Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.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.