Manish Yadav

WORK HISTORY

EDUCATION

ABOUT MANISH YADAV

Senior Data Scientist with 5+ years of industry experience in time-series analysis, demand forecasting, and advanced analytics, building scalable and explainable forecasting systems for e-commerce and retail use cases. Strong background in sequential and hierarchical forecasting, forecast diagnostics, and decision-grade analytics.Key Skills & ExpertiseProgramming & AnalyticsPython, SQL, Statistical Modeling, Feature Engineering, Exploratory Data AnalysisTime Series & ForecastingTime-series forecasting, demand sensing, hierarchical forecasting (SKU / category / brand), seasonality modeling (weekly, monthly, yearly), lag & rolling features, bias and stability optimizationMachine LearningTree-based models (Random Forest, XGBoost, LightGBM), regression models, classical time-series models (ARIMA, ETS), model evaluation and monitoringE-Commerce Demand ForecastingPromotions & pricing impact, holiday effects, demand shocks, sparse SKU modeling, global vs local forecasting strategies, forecast reconciliationLLM & Agentic AnalyticsLLM-enabled analytical workflows, agent-based systems for data extraction, planning, RCA, and code generation; human-in-the-loop validation for governed automationForecast Diagnostics & RCAData quality checks, feature behavior analysis, root cause analysis frameworks, explainability and monitoring for production forecasting systemsCloud & MLOps (Azure)Azure ML ecosystem, model deployment pipelines, experiment tracking, CI/CD, monitoring, scalable analytics workflowsProject Ownership & Stakeholder ManagementEnd-to-end project delivery from problem definition to production, cross-functional collaboration with business, supply chain, and engineering teams—Responsibilities & Impact • Designed and deployed end-to-end demand forecasting pipelines for e-commerce, balancing accuracy, bias, and forecast stability • Built RCA and forecast diagnostics frameworks to improve explainability and trust in forecasting outputs • Led development of agent-based analytics systems to automate exploratory analysis and validation workflows • Delivered production-ready solutions on Azure, ensuring scalability, monitoring, and governance • Owned multiple forecasting initiatives, driving alignment between analytics, engineering, and business stakeholders-Interests • Advanced time-series modeling & demand forecasting • Intelligent analytics using LLMs and agentic systems • Explainable AI, governance, and decision-centric ML • Building practical AI systems that scale in production