Analytics and Data Science - Retail / E-commerce

Who is this for

Fornax is seeking an exceptional Data Scientist who combines advanced analytical techniques with strong business acumen to drive measurable impact in the Retail and Ecommerce domain.

This role is ideal for professionals who are passionate about building sophisticated statistical models, conducting rigorous causal analysis, and translating complex methodologies into actionable business insights.

The ideal candidate excels at causal inference, experimental design, and predictive modeling while maintaining the ability to communicate technical concepts effectively to diverse stakeholders across the organization.

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
• Develop Marketing Mix Models (MMM) and attribution models to measure the incremental impact and ROI of marketing campaigns across channels, optimize budget allocation, and quantify the contribution of business initiatives

Statistical Modeling & Machine Learning (25%)

Experimentation & Testing (20%)

Strategic Decision Support & Communication (25%)

Key Skills

Technical Skills

Education & Experience