Vijayan Shinde

Designed and implemented a primal-dual optimization algorithm for dynamic pricing under inventory constraints. Built ML models for demand estimation, achieving ~85% forecast accuracy. Evaluated 10,000+ scenarios, reducing pricing gaps to within 10% of optimal. Built dashboards visualizing pricing, demand, and revenue metrics for cross-functional stakeholders.

Started in backend software development (SAP ABAP), customizing business logic and processes. Transitioned into Data Analytics, owning end-to-end workflows from data sourcing to dashboarding Built scalable Python data pipelines, ensuring data quality across the reporting lifecycle Automated ETL workflows in Google BigQuery to support faster, data-driven decisions Developed interactive Power BI dashboards translating complex data into clear KPIs for cross-functional stakeholders

Analyzed simulation data to identify relationships between process parameters and material properties Built predictive models validated against existing engineering results Ran structured parameter sweeps to support data-driven process optimization Translated findings into Power BI dashboards for stakeholders