Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

Design, build, and operate a low-latency online feature store and supporting batch/streaming pipelines. Optimize Postgres schemas and real-time serving for ML models, improve scalability, reliability, and observability, mentor junior engineers, and partner with data science, analytics, product, and application teams to deliver production-grade MLOps solutions.