Rishika Handa

Manager, Data Science

Impossible Foods•  July 2022 - October 2022

-----Strategy & Biz Ops Data Science Consulting (Python | Machine Learning | Product Management) ● Recommended product price variation strategy to optimize revenue by modeling consumer price elasticity using transaction data ● Performed benchmarking for metrics like inventory turn, cost-to-cost cycle, logistics cost, etc to identify key business anchors for helping prioritize improvement efforts in the supply chain ● Improved process efficiencies and reduced operational expenses across multiple business divisions within the company working as a cross-functional Data Science Consultant ● Built a clustering model to segment 1000+ acres of land mass using features like slope, NDVI index & satellite image data to enable a large scale control-treatment experiment for identifying carbon credit potential through different plantation protocols using Machine Learning

Data Science S&OP

Impossible Foods•  May 2021 - July 2022

----- Monte Carlo Simulation forecasting: (Python | Predictive Analytics | Monte Carlo Simulation | Long-range forecasting) ● Modeled long-range forecast for 5 business units to drive strategic long-term capacity expansion decisions using Monte Carlo simulation ● Optimized forecasting model accuracy by iteratively adapting to business changes and enriching the feature set used for model training International Channel demand forecasting: (S&OP forecasting | Advanced excel | Demand Planning) ● Established the end-to-end S&OP process for the International business channel, by aligning teams across 6 different countries ● Orchestrated coherence between Material Planning, Field Operations, Inventory Management, NPI, Production, Product Planning, and Sales team for gathering data and insights on key business drivers to influence the demand/supply balance for International SKUs ● Improved the demand forecast accuracy by analyzing historical consumption data and incorporating trends and consumption patterns using advanced statistical models and time series analysis ● Acted as an SME for implementing the International Forecasting module in an Integrated Business Planning tool - o9 Solutions

Statistical Analyst

Post Holdings•  September 2019 - May 2021

------ Statistical Modeling and Demand planning: (R | Predictive Analytics | SARIMAX | Grid Search | Cross Validation) ● Improved consensus forecast accuracy by modeling consumption data using a time-series model (SARIMAX) to predict SKU-level demand ● Improved the demand accuracy by 20% by incorporating statistical forecasting within the IBP process for high velocity SKUs ● Reduced manual demand forecasting efforts (-10%) by automating forecast generation in Integrated Business Planning tool - o9 solutions ● Reviewed statistically generated demand forecasts and tuned statistical parameters to guide the Demand Planning team Network Optimization: (Optimization | Gurobi | Python | Simulation Modeling | Data Modeling) ● Developed an MIP Optimization model to generate constraint-based & operations-cost-optimized supply plan mappings, between products, co-manufacturers and warehouses using Python and Gurobi Solver ● Generated offline evaluations resulting in $3M+ savings in total operations cost (Network Optimized vs Actual previous fiscal year) ● Facilitated the enablement of the Network Optimization strategy with Supply Planning, Deployment, and Manufacturing teams System Maintenance and Ad-Hoc Data Analysis: ● Investigated and refined data integrity between Business Operations & o9 - Solutions to maintain coherence & bug-free functionality