- Deconstructed and quantified the impact of key factors (pricing, promotions, activations, spend, and competitors) on sales
- Analyzed the ROI and uplifts to recommend the ideal discount depth across 8 retailers and 3 brands under a strict deadline
- Generated promo elasticity curves to define promo coefficients (delineating the effect seasonality, competitor, cannibalization) for 100+ SKUs by leveraging advanced regression models like Elastic-net, Huber, GLMnet with 85% accuracy
- Delivered insights on identifying and mitigating toxic/margin-diluting promotions, while optimizing volume/margin uplifts and trade spend efficiency with a resultant incremental margin of approximately $1m on $5m in promotions spend
Senior Data Scientist Impact Analytics India
November 2021 - December 2022
Trainee Decision Scientist Mu Sigma India
September 2018 - October 2021
Skills
A/B TestingAlgorithmsAnalytical ThinkingAnomaly DetectionArtificial IntelligenceAttention to DetailAutomationBenchmarking SkillsBrand ManagementCalculationsChain StoresCloud ComputingCluster AnalysisComputer ProgrammingDashboardsData AnalysisData IngestionData MiningData ProcessingData ScienceData TransformationDeep LearningElasticityElectronicsForecasting SkillsHairstyling and Hair CareInformation TechnologyInstrumentationKnowledge of EngineeringKnowledge of StatisticsLeadershipLogistic RegressionMachine LearningMarkovMicrosoft ExcelNatural Language ProcessingPharmaceuticalsPower BIPredictive ModellingPrincipal Component AnalysisProblem SolvingPython (Programming Language)PytorchQliksenseRetail CommerceSalesSales PromotionSample Size DeterminationSelf MotivationSimulationsSnowflakeSQL DatabasesStatistical Hypothesis TestingStock Keeping UnitStrategies of PricingTableau (Software)TensorflowTime SeriesTreatment and Control GroupsVisualization