I don't just analyze data — I build systems that make decisions smarter. From MILP models that schedule 40+ trains a day to ML pipelines that estimate EV battery health.
My work spans forecasting, mathematical optimization, simulation, machine learning and NLP — applied to transportation, supply chains, inventory planning and intelligent systems.
MILP, train scheduling, resource allocation — PuLP, CPLEX & Gurobi at industrial scale.
Dashboards, KPI tracking and business intelligence with Power BI, Tableau & SQL.
OTIF analysis, demand forecasting and inventory planning across FMCG & retail data.
Churn prediction, classification and large-scale text preprocessing pipelines.
SOH estimation, drive-cycle analysis and thermal data modeling for electric vehicles.
Land-use mapping and regional planning with QGIS & OpenStreetMap.
Plotted like a train timetable — because I literally schedule trains.
Every project below shipped with a measurable result — not just a notebook.
Deep Q-Learning vs Webster's-formula MILP for a 4-way intersection under Indian mixed-traffic — custom simulation with cars, bikes, buses & autos.
Freight-prioritized MILP scheduling model for Chakradharpur Division using real Working Time Table data — single-line & junction constraints.
Binary sentiment classifier trained on 1.6M tweets — full pipeline from raw text to TF-IDF to Logistic Regression, deployed as a live Streamlit app.
ARIMA/Prophet time-series forecasting with reorder alerts, backed by Power BI dashboards for inventory & product-level planning.
Discrete-event simulation with routing optimization — worker allocation and layout redesign for measurable throughput gains.
OT%, IF% & OTIF% service-level KPI analysis for AtliQ Mart across 6 product categories — logistics bottlenecks affecting contract renewals.
ILP framework scheduling 50+ tasks across 10 resources with precedence constraints, capacity limits and Gantt visualization.
Scraped & structured the largest US companies by revenue — Requests + BeautifulSoup extraction, Pandas cleaning, production-ready CSV output.
3NF normalized relational schema for 8 entities, with 15+ SQL queries for revenue trends and customer segmentation.
Open to roles in Business Analytics, Operations Research, Supply Chain Analytics & Data Analytics — anywhere the work involves real problem-solving, not just reporting.