Business Analyst/Manager- Revenue Growth Management

Key Responsibilities

• Build and refine price elasticity models, promotional uplift models, and demand forecasting frameworks using retailer POS/sell-out data/syndicated data/Sell-In data
• Build and refine price and promotion optimization models
• Contribute to the development of a reusable, parameterized modelling framework that can be deployed across multiple markets with minimal rework
• Work with RGM SMEs to translate commercial questions into modelling briefs and validate outputs for commercial sensibility
• Collaborate with data engineers to define data schemas, feature requirements, and model-ready dataset specifications
• Document modelling assumptions, validation results, and known limitations clearly for both technical and business audiences
• Support deployment and handover of models to client teams, including technical documentation and user guides
• Proactively flag data quality issues and modelling risks to the project lead

Qualifications — Required

• Master's or equivalent in Statistics, Economics, Data Science, Operations Research, or a related quantitative field
• 4–14 years in applied data science, with at least 2 years focused on pricing analytics, promotion effectiveness, or revenue management in CPG or Retail
• Hands-on experience building price elasticity models and/or promotional lift/uplift & Optimization models in a commercial context
• Familiarity with sell-out or POS data from syndicated providers (Nielsen, IRI/Circana) or direct retailer feeds
• Proficient in Python (scikit-learn, stats models, XGBoost) and SQL
• Experience with cloud analytics platforms (Databricks, Snowflake, or equivalent)
• Ability to communicate modelling results clearly to non-technical stakeholders