Vedant Vijay Shinde

Create a multi-city analytics architecture that standardizes fairness metrics, decile ranks, and peak/off-peak service patterns across 12+ cities, enabling faster cross-region comparisons and more consistent decision-making for transportation planners

Produce Python-driven visuals—including drift indicators, mismatch maps, and infrastructure-to-usage overlays—that uncover localized service gaps, empowering stakeholders to prioritize deployment and reduce underserved-zone complaints

Streamline operational reporting by building an automated workflow that generates 15+ geospatial and supply–demand visuals per city, cutting manual analysis time and supporting rapid iteration during policy reviews

Constructed a large-scale ETL pipeline (Python + AWS EC2) to ingest and clean millions of real-time mobility records from 8 systems, improving data reliability and enabling teams to run downstream analytics without pipeline failures

Engineered geospatial and statistical models that exposed 30% lower vehicle availability in disadvantaged neighborhoods, giving leadership a measurable basis for rebalancing fleet allocation and reducing wait times

Synthesized temporal, supply, and demand KPIs into dynamic Power BI dashboards that highlighted peak-hour shortages, helping resource teams plan capacity improvements tied directly to predicted rider spikes

Implemented an SQL-driven auditing system tracking 500+ vendor purchase orders, flagging discrepancies and reducing supplier- related delay escalations by giving procurement clear visibility into order reliability

Extracted workflow bottlenecks by analyzing 200+ unstructured operational notes, guiding department leads to revise processes

Identified 18 high-value product affinity patterns from 5,000+ transactions, informing a new store-layout strategy that increased bundle opportunities and improved promotional targeting