Data Scientist
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Job Description
Data Scientist leading AI/ML initiatives and strategy at Capgemini Engineering. Develop and productionize models for pricing and demand forecasting in an innovative environment.
Responsibilities:
- 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
Requirements:
- 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
Benefits:
- 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.
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