Rudransh M

Tax Automation through GenAI

EY • Part-time

Jul 2025 - Dec 2025 • 5 mos

One example was when a client was struggling with a Python-based data processing application that kept crashing due to inconsistent CSV formats and missing values. The issue was time-sensitive because the client relied on the application for daily reporting. I first reproduced the problem on my local environment and analyzed the input files instead of immediately modifying the code. I identified that the application assumed identical column names and clean data across all CSV files, which wasn't true. I redesigned the import logic to automatically map similar headers, validate missing fields, handle malformed rows gracefully, and generate meaningful error messages instead of crashing. I also optimized the processing pipeline, reducing execution time significantly for large datasets. Throughout the process, I kept the client updated with clear explanations of the root cause, the progress being made, and how the final solution would prevent similar issues in the future. After deployment, the application processed the client's datasets without errors, eliminated the need for manual corrections, and reduced processing time by more than 50%. The client appreciated both the technical solution and the transparent communication, leading to positive feedback and continued trust in my support.