Summary
Abhirup Ghosh is a Senior Data Scientist based in Berlin with a decade of experience bridging physics research and production-grade machine learning for high-stakes domains. He transitioned from leading influential gravitational-wave data analysis at LIGO—where his open-source pipelines and Bayesian methods contributed to scores of discovery papers—to building real-time AML, fraud detection, and customer-risk systems in fintech. At emmy sharing he scaled BI and forecasting infrastructure, delivered sub-percent rental forecasts, and enabled a major acquisition through data-driven strategy while cutting costs with computer-vision enrichment. Technically fluent across Python, PyTorch, Snowflake, Airflow, Metaflow and SageMaker, he combines deep expertise in graph neural networks and real-time systems with hands-on MLOps experience. Unusually for a data scientist, his publication record and editorial roles in collaborative physics experiments inform a rigorous, reproducible approach to model validation and governance.
10 years of coding experience