Job Duties & Responsibilities: Work with large and complex financial datasets to develop end-to-end data science solutions for pricing various financial products, dynamic campaign optimization, and customer personalization. Conduct research and literature review to assess and evaluate trade-offs between different quantitative algorithms and models. Implement and train AI/ML models and optimize algorithm efficiency (GPU distributed computing, concurrent programming) Refactor and document code into reusable libraries/ APIs/ tools, deploy machine learning ecosystems, and perform sub-system integration as required. Integrate solutions into enterprise MLOps ecosystem and automate CI/CD pipelines for model lifecycle maintenance and monitoring. Requirements: Good understanding of the data science production life cycle with demonstrable experience working with structured, semi-structured and unstructured data. Excellent software skills (Python, SQL variants) and knowledge in design patterns, c...