Sripada Venkata Pradyumna

I am a Data Science graduate student at the University of California, San Diego, with a top-ranking Bachelor's in Computer Science. My professional experience bridges advanced academic research with practical, high-impact industry applications.

At Simpl, I analyzed a $7B portfolio to enhance partial payment conversions and built clustering models to boost fraud detection precision by 6%. During my internship at IBM Research, I developed an LLM-based log classification pipeline that improved accuracy by 15% over fine-tuned BERT models and created data validation tools to detect synthetic data drift.

I thrive on solving complex problems, whether it's modeling climate risk for the Fiji Development Bank or developing novel architectures for unsupervised person re-identification. I am proficient in Python, SQL, and a wide array of data science and MLOps tools, and I am always eager to learn and apply new technologies to drive meaningful results.