Global APAC lead- RGM transformation

• Developed E2E scalable framework for Revenue Growth Management from model building to ROI estimation, simulation and optimization across 14 markets for a fortune 200 Major• Managing Product Roadmap for inhouse Consumer Analytics product

• Incubated PoC concept into a scalable architecture & product and received US patent grant for the underlying NLP based technology framework• Leading a team 10+ through agile scrum methodologiesConsulted for a Fortune 200 CPG major in 3 year brand strategy planning exercise on ecommerce strategy onsite at client headquarters

Played a vital role in Ecommerce project on Consumer Purchase Journey tracking for a Fortune 200 major that gave top results for the client business. • Achieved +20% versus baseline (+30% vs PY) Net revenue• Gain in market share around 15% in tested category• High single digit gross margin expansion through better segmentation and channel shifts• Generated the best ever month, including Prime days month, in history of client owned products sale in Amazon.• Developed end to end R shiny based solution from design to deployment for unstructured NLP data processing and insight generation. • Converted above PoC concepts into a scalable architecture and a product.• Consulted for a Fortune 200 CPG major in 3 year brand strategy planning exercise on ecommerce strategy onsite

Developed end to end solution for identifying the right SKUs that can be added or removed from a store and create weekly orders with optimised volume at store X SKU level • Proposed and implemented PAM clustering technique to segment stores to set benchmarks and estimate opportunities.• Implemented parallel processing to achieve massive performance gains and reduced processing time.• Deployed the solution to run automated and at scale ( ~2 lakh stores ) with weekly order refresh, removing any need for user intervention.• Innovated a one stop solution for Bayesian regression modelling, visualization and simulation using R shiny.• Created an easy to use GUI for adding variables to model with the help of residual correlation tables aided with actual vs predicted charts.• Designed and built an interactive consumption layer providing model due-to’s, contributions, price curves, S/C curve-based optimizations and simulator.