
location_onGrace Street Commercial Historic District, Byrd Street Cycle Track, Richmond, Virginia, 23284, United States
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 relational databases 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 leading the next wave of disruption at a whole new scale. You will use the latest in computing and machine learning technologies, operating across billions of customer records to unlock big opportunities that help everyday people save money, time, and agony in their financial lives.
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). We strive to achieve optimal results for both Risk Management and the broader Enterprise by learning from past errors to develop increasingly robust techniques that prevent recurrence.
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. You will leverage a broad stack of technologies to reveal insights hidden within huge volumes of multi-modal data, build machine learning models to challenge "champion models" deployed in production, and contribute to the model governance framework for the next generation of models.
You will validate a wide variety of models across multiple business domains within our Enterprise Services division. A key part of your day involves flexing your interpersonal skills to present how identified model risks could impact the business to executives, ensuring that data science solutions are both technically sound and business-aligned.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. This role is eligible to earn performance-based incentive compensation, which may include cash bonuses and/or long-term incentives. Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well-being.
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. We promote a drug-free workplace and will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws.
If you require an accommodation to apply for a position, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and used only to the extent required to provide needed reasonable accommodations.
Skills: Pytorch, Hugging Face, Langchain, Vector Databases, Llmops, Aws, Python, Scala, R, Machine Learning.
Education: Bachelor's Degree in a quantitative field required; Master's Degree in a quantitative field or MBA with quantitative concentration required; Master's Degree in STEM field preferred.
Work model: On-site
Grace Street Commercial Historic District, Byrd Street Cycle Track, Richmond, Virginia, 23284, United States
Richmond, Virginia
Master's Degree or PhD in a STEM field (Science, Technology, Engineering, or Mathematics). Experience working with AWS. At least 2 years' experience in Python, Scala, or R for large scale data analysis. At least 2 years' experience with machine learning.
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