Senior Director, Data Science

Capital One•McLean, VA

2d•Remote

About The Position

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 Science Leader 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. About the Team We're building a portfolio of agentic AI products to transform Capital One's engineering organizations and lines of business – autonomous coding agents, context engineering, and agentic model-development lifecycle to name a few. We're creating a new science team to help define the long-term strategy, analyze & optimize impact throughout the ecosystem, and drive business value at enterprise scale. As a scientist on the team, you'd design AI/ML models and help build the solutions behind these products. You'd also own the science that guides them: designing experiments (A/B tests), modeling telemetry, and turning the results into AI strategy and guidance for C-suite leadership.

Requirements

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 11 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 9 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 6 years of experience performing data analytics
At least 6 years of experience leveraging open source programming languages for large scale data analysis
At least 6 years of experience working with machine learning
At least 6 years of experience utilizing relational databases

Nice To Haves

PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
At least 6 years of experience in Python, Scala, or R for large scale data analysis
At least 6 years of experience with machine learning
At least 2 year of experience working with AWS
At least 6 years of experience with complex architectural patterns (SOA), building APIs, microservices, and event streams
At least 6 years of experience with DevOps or DevSecOps and building CI/CD pipelines using Jenkins, Artifactory, Chef, Ansible, AWS CloudFormation templates, GitHub, and Sonar

Responsibilities

Partner with a cross-functional team of software engineers, distinguished researchers, and solutions architects to drive great decisions through modeling
Define and drive towards an end state that is based on simplicity and the adoption of digital technologies, cloud hosting, and open source software.
Distill the details of complex interconnected modeling systems to influence senior business leaders on model strategy, business use, and risks
Assess, challenge, and at times defend state-of-the-art decision-making systems to internal and regulatory partners
Shape our practice of building machine learning models, from design through training, evaluation, validation, and implementation
Oversee development of benchmark and challenger models to stress test critical modeling decisions