Lead Data Scientist - RGM

We are looking for an experienced Lead Data Scientist with strong expertise in Machine Learning, Statistical Modelling, Forecasting, and Optimisation, along with hands-on experience in CPG / Retail Revenue Growth Management (RGM). The ideal candidate should have worked extensively on demand forecasting, price/promotion elasticity, forecast-driver attribution, time-series anomaly detection, and constrained optimization/simulation.
Responsibilities:
Design and develop advanced ML and statistical models for CPG/Retail RGM use cases.
Build scalable demand forecasting models across products, channels, customers, and geographies.
Develop price and promotion elasticity models to measure pricing and promotional impact.
Perform forecast-driver attribution to identify key factors influencing demand and sales.
Build time-series anomaly detection solutions for demand, sales, pricing, and promotional patterns.
Develop constrained optimisation and simulation models for pricing, promotions, revenue, volume, and margin decisions.
Perform large-scale data analysis using Python and SQL.
Translate complex analytical findings into actionable business recommendations.
Collaborate with Product, Engineering, Analytics, and business stakeholders.
Provide technical leadership and mentor Data Scientists.
Requirements:
7-10 years of relevant Data Science / Machine Learning experience.
Strong hands-on expertise in Python and SQL.
Strong knowledge of Machine Learning, Statistical Modelling, Data Analysis, and Time-Series Modelling.
Proven hands-on experience in: Demand Forecasting, Price and Promotion Elasticity, Forecast-Driver Attribution, Time-Series Anomaly Detection, Constrained Optimisation / Simulation.
Strong understanding of pricing, promotions, demand drivers, revenue, volume, and margin optimisation.
Strong analytical and stakeholder communication skills.
Mandatory Domain Requirement
Strong hands-on experience in CPG / Retail Revenue Growth Management (RGM) is mandatory.

Experience
7-10 yrs