Senior Data Scientist

Company DescriptionSince launching in Kuwait in 2004, talabat has become the region’s leading on-demand delivery app, serving millions of customers across eight countries. Our Quick Commerce (QC) Hub powers the grocery and convenience delivery experience — getting everyday essentials to customers’ doors in minutes, not hours.Behind every delivery is data. Our QC data team works at a scale most data scientists only read about: millions of daily transactions, thousands of partners, and decisions that directly shape how people across the Middle East get their groceries delivered. We’re building an analytics-first culture where every product and business decision is grounded in evidence.Your mission: ship the AI and ML systems that power talabat's intelligence. You're AI-native by default. You use Claude, Cursor, and equivalent tools as core leverage in how you architect and deploy. This is not a research role; we measure success in business outcomes and production reliability.You own a domain end to end — from problem framing through data pipelines, model training, deployment, and monitoring in production. You work closely with product and business teams, and you mentor other data scientists in their growth.Responsibilities:Frame ambiguous business problems as well-defined ML problems with clear success criteria.Design, build, and ship end-to-end ML and generative AI systems in production. You handle data pipelines, feature engineering, model training, serving, and monitoring without handoffs.Architect robust ML-based systems. Write clean, scalable production code. Train, deploy, and maintain reliable models.Leverage LLMs and generative AI for data enrichment, content understanding, and automated decision-making within production systems.Design and analyse experiments rigorously (A/B and multivariate tests) to measure model and product impact.Develop deep familiarity with source data and its generating systems through collaboration with engineering teams and systematic profiling.Provide high-quality insights and data-driven recommendations to drive strategic organisational choices.Mentor other data scientists. Elevate engineering and ML best practices — improving our ways of working, tooling, MLOps, and internal training.What we're looking for:3+ years shipping production ML systems (generative AI, recommendation engines, or ML infrastructure). Demonstrated velocity and ownership.Strong software engineering fundamentals: clean code, solid grasp of data structures, and system design (both general and ML-specific).Hands-on with the ML lifecycle: problem formulation, data auditing, modelling, deployment, interpretation, presentation.Proficiency in Python and SQL. Comfort with reproducible analysis and experimentation (A/B and multivariate analysis). Solid statistical thinking.Experience building data and training pipelines (Airflow or equivalent). Strong feature engineering and data modelling skills.Production ML systems experience: building, deploying, serving, monitoring. You understand MLOps practices.Familiarity with product data (events, impressions, conversions, engagement, retention). You know how to measure product health.Experience with LLMs and NLP-based solutions for data enrichment and automation is a plus.BigQuery or equivalent cloud data warehouse experience is a plus. GCP familiarity is a plus but not required.