Priyanshu Bansal

Leveraged SQL and Python to analyze export/import trends and competitive dynamics for cardiovascular drugs in the South Korean market, identifying key growth opportunities across 3 priority products and emerging molecules. Designed interactive Power BI dashboards for the BU heads to visualize Volume and price trends across 3 priority products. Performed cohort and trend analysis to segment performance over time and across product groups, conducted variance analysis and visualized seasonality across the FY 23 and FY 22.

Assistant Manager - Marketing - Cadchem Laboratories

(2023-07 - 2024-05)

• Leveraged SQL and Python to analyze export/import trends and competitive dynamics for cardiovascular drugs in the South Korean market, identifying key growth opportunities across 3 priority products and emerging molecules.
• Designed interactive Power BI dashboards for the BU heads to visualize Volume and price trends across 3 priority products.
• Performed cohort and trend analysis to segment performance over time and across product groups, conducted variance analysis and visualized seasonality across the FY 23 and FY 22.
• Automated reporting and KPI tracking frameworks, reducing manual analysis effort and enabling faster, data-driven decision-making for business stakeholders.

Intern - Thermax Ltd

(2026-01)

• Prototyped an Agentic AI Chatbot using LangChain and Llama 3.3 for solving vendor payment queries; currently scaling to enterprise-level using Python-based analytical solutions.
• Led cross-functional collaboration between Finance and AI/ML teams to design and implement 5+ AI-driven optimization use cases (Vendor Payment Chatbot, OCR, banking data summarization), improving process efficiency.
• Engineered a Risk Analytics dashboard in Power BI using Dax based fuzzy matching techniques to detect duplicate vendor payments and employee reimbursement claims, identifying ~₹2L in fraud across two financial years.
• Established a centralized Variance analysis dashboard (FY 26 VS FY25) integrating trial balance and transaction-level data, enabling granular analysis of revenue, expenses, and contribution across business segments for leadership review.

Intern - Reliance Retail

(2025-05 - 2025-07)

• Developed an AutoML-based product ranking system across 50+ brands using 15+ engagement metrics, improving recommendation accuracy by 18%.
• Shipped a Streamlit app for product insights, enabling non-technical teams to make data-driven decisions and reducing analysis time.
• Conducted EDA on customer and product data, identifying key trends that improved campaign targeting efficiency by 20%.

MBA - Business Analytics - Birla Institute of Technology and science, Pilani (2024 - 2026)

BE - Computer Science - Chitkara University (2019 - 2023)