Owning end-to-end model development for pricing, demand forecasting, and elasticity estimation; productionizing models in Azure ML and Databricks
Implementing prescriptive analytics through optimization with Linear Programming, Mixed Integer Programming or Reinforcement Learning
Implementing and maintaining feature stores, model monitoring workflows, and drift checks using MLflow (metrics, alerts, lineage)
Designing and executing A/B tests or quasi-experiments to measure revenue, pricing uplift, and PCP attach rate impact
Applying SHAP/LIME and other model interpretability tools to explain drivers of model behavior to Revenue Management partners

2–4 years of hands-on Data Science experience delivering production-grade ML solutions
Proficiency in Python (scikit-learn, XGBoost), Spark/Delta, SQL, Azure ML, Databricks, and MLflow; familiarity with PyTorch or TensorFlow is a plus
Strong understanding of experimental design, statistical testing, and causal inference basics
Ability to translate technical concepts into actionable business insights; skilled in stakeholder alignment and cross-functional communication
Experience communicating insights, assumptions, risks, and trade-offs in clear, concise, and executive-ready narratives

Empowering environment : Autonomy and Goal setting are among the top scores with 8,4+ ratings in our monthly employee feedback Pulse.
Dedicated innovation labs : We help the world's largest innovators engineer the products and services of tomorrow by leveraging our experts and labs, dedicated to topics as 5G, 6G, AI, Autonomous Vehicles and Quantum.
Communities : Our Framework drives career development and elevates Capgemini's capabilities across various domains.

Data Scientist

Key skills