Senior Manager, Data Science - Model Risk Office

Senior Manager, Data Science - Model Risk Office

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

The Capital One Model Risk Office is dedicated to safeguarding the company from model failures while simultaneously enhancing decision-making through models, including unique risks associated with Generative AI (GenAI). Leveraging expertise in statistics, software engineering, and business, we strive to achieve optimal results for both Risk Management and the broader Enterprise. We prioritize long-term success by continually investing in future capabilities: acquiring new skills, developing superior tools, and cultivating strong relationships with trusted partners. Our approach involves learning from past errors to develop increasingly robust techniques that prevent recurrence.

Role DescriptionIn this role, you will:

• Partner with a cross-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models

• Leverage a broad stack of technologies — from foundational frameworks (PyTorch, Hugging Face), to orchestration tools (LangChain, Vector Databases) to LLMOps, observability platforms, and more — to reveal the insights hidden within huge volumes of multi-modal data

• Build machine learning models to challenge “champion models” that are deployed in production today and contribute to the model governance framework for the next generation of models

• Validate a wide variety of models across multiple business domains within our Enterprise Services division, and flex your interpersonal skills to present how identified model risks could impact the business to executives.

The Ideal Candidate is:

• Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.

• Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.