Souhardya Chattopadhyay

-> Engineering data product ETL pipelines within the Siemens Data Cloud utilizing dbt, Snowflake, and AWS to enable scalable analytics and cross-departmental data availability. -> Developed and optimized multiple interactive Power BI dashboards and underlying semantic models to streamline executive financial reporting and portfolio monitoring. -> Applied ML-based time-series forecasting models to analyze sensor data of EV charging substations. -> Implemented automated multi-source data validation detecting

-> Benchmarked time-series Foundation models (Chronos-2, Chronos-bolt) against ML and statistical baselines on 50,000+ smart meters across Zip, Substation, and LV-feeder levels, building scalable short-term load forecasting pipelines for peak-focused grid risk mitigation. -> Validated model performance robustness by conducting Clustering and Seasonal analysis. -> Derived optimal operating quantiles per level for probabilistic foundation models, improving performance over ML models during extreme load events

Master Thesis in collaboration with Siemens AG.

-> Launched global sales dashboards on Qlik and conducted in-depth funnel and booking trend analysis for internal teams worldwide, reducing manual report generation by ~70%. -> Formulated a statistical market forecasting model leveraging global and regional sales data to predict revenue and order growth, supporting long-term strategy and portfolio planning.

-> Delivered 15+ BI dashboards on cloud platforms and automated daily report generation tracking volume, peak hours, and key demand metrics across supply chain operations. -> Developed ad-hoc Python scripts and SQL queries in an agile environment for real-time root-cause analysis on operational escalations, optimizing resource allocation and overall ROI. -> Analyzed core operational metrics such as growth, efficiency, loyalty, priority localities, and marketing initiatives for complex 30-min intra-city logi

-> Worked on Projects related to Ecommerce clients such as Flipkart, Myntra, Meesho, Ajio, etc., contributing to the reports such as Node Service Level performance (NSL), Shipped to Attempt Time (S2A), Client Promised Time (CPT) and related metrics. -> Developed python codes to automate reports related to TAT and Hygiene Metrics. -> Performed analysis on Zone and Pincode Servicibility, Order Flow, Pickup to First Attempt Time, performance at First Mile, distribution centers (DC), middle mile and and Last mi