Found Description
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 PyTor...