Summary
Aniruddha Dutta is a Lead Data Scientist based in Berkeley with eight years of experience building ML and generative AI solutions for finance, risk, and fraud detection. He combines a PhD in Physics and an M.S. in Financial Engineering to translate rigorous quantitative research into production-grade models and MLOps pipelines at firms like SimCorp, Axioma, Scotiabank and SumUp. His expertise spans LLM fine-tuning, RAG, vector search, PyTorch/TensorFlow, and deployment on platforms such as Databricks, Vertex AI and Kubernetes, enabling end-to-end systems from prototype to scaled inference. Notably, he has boosted NLP summarization efficiency and default-prediction performance on 100K+ documents, and cut fraud false positives through graph neural networks and classical ensembles. He’s equally comfortable designing differential-equation solvers from his academic work as he is architecting agentic GenAI flows, giving him a rare blend of theoretical depth and applied engineering. Colleagues rely on him to turn complex financial problems into auditable, high-impact analytics and production services.
8 years of coding experience
14 years of employment as a software developer
MSc Engineering Physics/Applied Physics, MSc Engineering Physics/Applied Physics at Indian Institute of Technology (Indian School of Mines), Dhanbad
Masters Financial Engineering, Masters Financial Engineering at University of California, Berkeley, Haas School of Business
Bachelor's degree Physics, Bachelor's degree Physics at University of Calcutta
Doctor of Philosophy - PhD Physics, Doctor of Philosophy - PhD Physics at University of Central Florida
Hindi, English