Manager, Data Scientist - SBB Marketing & Deposit Strategy

Capital One • McLean, VA

1d • $197,300 - $225,100

About The Position

Capital One’s Small Business Bank (SBB) Data Science team partners across the organization to optimize the performance and impact of financial products, policies, and services. The team applies statistics, machine learning, and emerging AI technologies to support small-business customers and their long-term success.

The Manager, Data Scientist will partner with data scientists, software engineers, and product managers to deliver customer-focused products. The role uses technologies such as Python, Conda, AWS, H2O, and Spark to analyze large volumes of numeric and textual data. It develops machine learning models through design, training, evaluation, validation, and implementation, and translates technical findings into business goals. A key focus is developing account-level lifetime value (NPV) models that forecast revenue and cost drivers to inform strategic decision-making across SBB.

The role calls for a technically capable, data-oriented, creative, and innovative professional who can work with open-source tools and cloud platforms, analyze data from varied sources and structures, bring definition to ambiguous problems, and stay current with emerging technologies and methods. Capital One will consider sponsoring a new qualified applicant for employment authorization. The role is eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives. The position is expected to accept applications for at least five business days.

Requirements

• Currently hold or be in the process of obtaining, by the scheduled start date, a bachelor's degree in a quantitative field and have at least 6 years of data analytics experience; or a master's degree in a quantitative field or an MBA with a quantitative concentration and at least 4 years of data analytics experience; or a PhD in a quantitative field and at least 1 year of data analytics experience.
• At least 1 year of experience leveraging open-source programming languages for large-scale data analysis.
• At least 1 year of experience working with machine learning.
• At least 1 year of experience utilizing relational databases.

Nice To Haves

• PhD in a STEM field plus 3 years of experience in data analytics.
• At least 1 year of experience working with AWS.
• At least 4 years of experience using Python, Dask, Spark, or similar tools for large-scale data analysis.
• At least 4 years of experience with machine learning and statistical modeling.
• At least 4 years of experience with SQL.

Responsibilities

• Partner with data scientists, software engineers, and product managers to deliver a product customers love.
• Use a broad technology stack, including Python, Conda, AWS, H2O, and Spark, to uncover insights in large volumes of numeric and textual data.
• Build machine learning models through design, training, evaluation, validation, and implementation.
• Translate complex technical work into tangible business goals.
• Develop account-level lifetime value (NPV) models that forecast revenue and cost drivers to support strategic decision-making across SBB.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being.
• Eligible for performance-based incentive compensation, potentially including cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager