Who is this for
If building sophisticated statistical models and conducting rigorous causal analysis to drive business impact excites you, this is your prospect. Fornax is seeking a Data Scientist who combines advanced analytical techniques with business acumen to solve complex challenges in the Retail domain.

We are looking for a technically proficient data scientist who excels at causal inference, experimental design, and predictive modeling while translating complex methodologies into actionable business insights.

Key Responsibilities

Advanced Analytics & Causal Inference (30%)
- Design and implement causal inference studies using difference-in-differences (DiD), regression discontinuity, synthetic control methods, and propensity score matching
- Conduct rigorous A/B testing and experimental design to measure treatment effects and validate business interventions
- Build predictive models using machine learning techniques (random forests, gradient boosting, neural networks) for customer behavior, demand forecasting, and churn prediction




- Perform time series analysis and forecasting for sales, inventory, and market trends
- Apply advanced statistical methods to identify and quantify causal relationships in observational data
- Develop attribution models to measure the incremental impact of marketing campaigns and business initiatives

Statistical Modeling & Machine Learning (25%)
- Build and deploy supervised and unsupervised learning models for classification, regression, clustering, and recommendation systems
- Implement feature engineering pipelines and model selection frameworks to optimize predictive performance
- Develop customer segmentation models using clustering algorithms and behavioral analytics
- Create price optimization and dynamic pricing models using elasticity analysis
- Build survival analysis models for customer lifetime value and retention prediction
- Apply natural language processing (NLP) techniques for sentiment analysis and customer

📌 Data Scientist (Mumbai)
🏢 Fornax
📍 Mumbai