Data Scientist

As a Data Scientist at Fornax, you will be responsible for building sophisticated statistical models and conducting rigorous causal analysis to drive business impact in the Retail domain. Your role will involve a combination of advanced analytical techniques and business acumen to solve complex challenges. **Key Responsibilities:** - Build and deploy machine learning models for pricing optimization, demand forecasting, and promotional response prediction - Develop predictive models using regression, decision trees, gradient boosting (XGBoost, LightGBM), and neural networks - Conduct causal inference analysis to measure true promotional incrementality and long-term effects - Perform market basket analysis and product affinity modeling - Create recommendation engines for product and promotion personalization - Implement A/B testing frameworks and experimental design for pricing and promotional strategies - Deploy models into production and monitor performance over time - Analyze portfolio performance and build SKU rationalization frameworks - Conduct gross-to-net revenue analysis and identify revenue leakage patterns - Build what-if scenario planning tools for pricing, promotion, and assortment strategies - Design Power BI dashboards to communicate model insights and predictions - Present findings to senior leadership with compelling data storytelling - Write SQL queries to extract and prepare data for modeling - Create automated reporting for model performance and business KPIs - Partner with commercial, finance, and marketing teams to define modeling requirements - Mentor junior analysts and data scientists on best practices **Qualifications Required:** - Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, Engineering, or related quantitative field - Experience: 3-6 years of experience in analytics or data science, with at least 2 years focused on Revenue Growth Management, pricing analytics, trade promotion optimization, or commercial analytics in Retail/D2C/FMCG/CPG domains - Expert-level Power BI: DAX, Power Query, data modeling, dashboard design, custom visualizations - Advanced SQL: Complex queries, window functions, CTEs, query optimization, performance tuning - Python/R Programming: Data manipulation (pandas, numpy), visualization (matplotlib, seaborn, plotly), statistical analysis - Machine Learning: Scikit-learn, XGBoost, LightGBM, TensorFlow/PyTorch basics - Statistical Analysis: Regression (linear, logistic, polynomial), hypothesis testing, A/B testing, experimental design If you are passionate about leveraging data science to drive business decisions and have the technical expertise to build and deploy advanced analytical models, this role at Fornax could be the perfect fit for you. As a Data Scientist at Fornax, you will be responsible for building sophisticated statistical models and conducting rigorous causal analysis to drive business impact in the Retail domain. Your role will involve a combination of advanced analytical techniques and business acumen to solve complex challenges. **Key Responsibilities:** - Build and deploy machine learning models for pricing optimization, demand forecasting, and promotional response prediction - Develop predictive models using regression, decision trees, gradient boosting (XGBoost, LightGBM), and neural networks - Conduct causal inference analysis to measure true promotional incrementality and long-term effects - Perform market basket analysis and product affinity modeling - Create recommendation engines for product and promotion personalization - Implement A/B testing frameworks and experimental design for pricing and promotional strategies - Deploy models into production and monitor performance over time - Analyze portfolio performance and build SKU rationalization frameworks - Conduct gross-to-net revenue analysis and identify revenue leakage patterns - Build what-if scenario planning tools for pricing, promotion, and assortment strategies - Design Power BI dashboards to communicate model insights and predictions - Present findings to senior leadership with compelling data storytelling - Write SQL queries to extract and prepare data for modeling - Create automated reporting for model performance and business KPIs - Partner with commercial, finance, and marketing teams to define modeling requirements - Mentor junior analysts and data scientists on best practices **Qualifications Required:** - Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, Engineering, or related quantitative field - Experience: 3-6 years of experience in analytics or data science, with at least 2 years focused on Revenue Growth Management, pricing analytics, trade promotion optimization, or commercial analytics in Retail/D2C/FMCG/CPG domains - Expert-level Power BI: DAX, Power Query, data modeling, dashboard design, custom visualizations - Advanced SQL: Complex queries, window