Data Science Manager

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 Description In 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. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond. Technical. You’re comfortable with open‑source languages and are passionate about developing further. You have hands‑on experience developing data science solutions using open‑source tools and cloud computing platforms. Statistically‑minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning. A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science. Basic Qualifications Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 years of experience performing data analytics A Master’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 5 years of experience performing data analytics A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics At least 2 years of experience leveraging open source programming languages for large scale data analysis At least 2 years of experience working with machine learning At least 2 years of experience utilizing relational databases Preferred Qualifications PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics At least 1 year of experience working with AWS At least 1 year of experience managing people At least 5 years’ experience in Python, Scala, or R for large scale data analysis At least 5 years’ experience with machine learning Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. Chicago, IL: $209,000 - $238,500 for Sr Mgr, Data Science McLean, VA: $229,900 - $262,400 for Sr Mgr, Data Science Richmond, VA: $209,000 - $238,500 for Sr Mgr, Data Science Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries. #J-18808-Ljbffr