Naman Shrivas

At Varada Farmers Producer Company, I analyzed business processes and datasets to identify inefficiencies and data-quality issues. I used Python and pandas to support process improvement and shared findings through recommendations and visual summaries.

At TechMahindra, I analyzed application logs and system metrics to investigate performance bottlenecks and root causes. This work improved system efficiency by 15%, while process improvements reduced error rates by 20%.

For my credit risk analytics project, I developed a platform using SQL and Python to analyze exposure, limits, ratings, risk mitigants, counterparty hierarchies, and reference data. I also implemented data-quality validation and root-cause analysis for issues such as missing records and exposure-limit exceptions.

I built an Excel and Power BI dashboard to monitor exposure, limit utilization, rating distribution, risk concentration, and data-quality exceptions. I’m pursuing an MBA in Data Science & Business Analytics and am interested in applying analytical and AI-assisted approaches to credit risk, data quality, controls, and regulatory change.