Tech Stack
CloudFlaskNumpyPandasPythonPyTorchScikit-LearnSparkSQLTensorflow
About the role
- Model and measure price elasticity of demand across products, categories, and customer segments
- Develop and test AI/ML models incorporating elasticity coefficients into demand forecasting and pricing scenarios
- Analyze structured and unstructured retail data to uncover trends and quantify customer sensitivity to price changes
- Apply statistical, econometric, and causal inference techniques to simulate what-if pricing and promotion strategies
- Build and iterate on prototypes and POCs integrating elasticity insights into real-world retail/CPG contexts
- Present findings through clear storytelling and data visualization to influence technical and business stakeholders
- Collaborate with engineering and product teams to bring data-driven solutions into production
Requirements
- Bachelors degree or higher in Econometrics, Operations Research, Applied Mathematics, Statistics, Data Science, or related field
- 5+ years of experience in retail or CPG with proven expertise in price elasticity modeling and demand forecasting
- Strong command of Python (pandas, NumPy, OOP) and SQL
- Demonstrated experience quantifying elasticity coefficients and applying them in business contexts
- Solid background in regression models, time-series forecasting, and causal inference
- Experience working with large, complex datasets and iterating prototypes with cross-functional teams
- Ability to communicate complex analytical insights to technical and non-technical audiences
- Familiarity with scalable cloud environments and distributed data systems
- English Level: B2 / C1