Senior Director, Data Science

Capital One; McLean (VA); On-site; USD 180,000 - 300,000; Full time

Job summary

Capital One seeks a Senior Director of Data Science to lead a team building AI-powered products and modeling strategies across billions of records. You will guide architecture, experimentation, and ML lifecycle from design to deployment, partnering with software engineers, researchers, and solution architects.

You will shape a strategy for scalable, compliant, and high-impact analytics while communicating complex results to executives.

Qualifications

• Bachelor's Degree plus 11 years of analytics experience;
• Master's Degree with quantitative focus or MBA with quantitative focus plus 9 years of analytics experience;
• PhD in quantitative field plus 6 years of analytics experience.
• At least 6 years of experience using open source 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.

Responsibilities

• Partner with cross-functional team to drive decisions through modeling.
• Define end state based on simplicity, digital tech adoption, cloud hosting and open-source software.
• Distill complex modeling systems to influence senior leaders on strategy and risks.
• Assess, challenge and defend state-of-the-art decision-making systems with internal/regulatory partners.
• Shape practice of building ML models from design to training, evaluation and implementation.
• Oversee development of benchmark and challenger models for critical decisions.

Skills

Open-source languages

Machine Learning

Relational Databases

Cloud Computing

Python/Scala/R

Education

Bachelor's degree with 11+ years data analytics

Master's degree with quantitative concentration or MBA

PhD in quantitative field

Tools

AWS

Jenkins

Artifactory

Chef

Ansible

GitHub

CloudFormation

Sonar

Job description

Senior Director, Data Science

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.

In this role, you will:

• 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

The Ideal Candidate is:

• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo.
• 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.
• 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.

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 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

Preferred Qualifications:

• 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

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

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