Manager, Data Science - US Card - Marketing

Capital One • McLean, VA

5d • $197,300 - $225,100 • Hybrid

About The Position

Capital One’s Marketing Data Science team develops advanced machine learning solutions to optimize customer acquisition. The team uses predictive models and reinforcement learning across marketing-funnel touchpoints to deliver personalized customer experiences and accelerate growth. It embeds model-driven insights across channels to support seamless, targeted engagement, using supervised and reinforcement learning to predict customer needs and recommend suitable solutions. The team writes custom Python libraries and uses open-source machine-learning libraries, including XGBoost, scikit-learn, and statsmodels. Its models guide treatments for millions of customers daily and run in analytical and production environments. The team works closely with campaign managers, business analysts, and engineering teams to deliver measurable business value and inform strategic decisions.

As a Data Science Manager, you will work with data scientists, software engineers, and product managers to develop customer-focused products. You will use technologies such as Python, Conda, AWS, H2O, and Spark to find insights in large volumes of numeric and textual data. You will develop machine-learning models across the full lifecycle, from design and training through evaluation, validation, and implementation, and communicate technical work in terms of tangible business goals.

This is a hybrid role. The employee is expected to follow Capital One’s hybrid policy for required on-site presence at their designated office location.

Requirements

• Have or be obtaining, with the required degree expected by the scheduled start date, a bachelor’s degree in a quantitative field plus 6 years of data analytics experience; a master’s degree in a quantitative field or an MBA with a quantitative concentration plus 4 years of data analytics experience; or a PhD in a quantitative field plus 1 year of data analytics experience.
• At least 1 year of experience using 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 using relational databases.

Nice To Haves

• A PhD in a STEM field plus 3 years of data analytics experience.
• At least 1 year of experience working with AWS.
• At least 4 years of experience using Python, Scala, or R for large-scale data analysis.
• At least 4 years of experience with machine learning.
• At least 4 years of experience with SQL.

Responsibilities

• Partner with data scientists, software engineers, and product managers to deliver customer-focused products.
• Use technology and analytical methods 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.
• Collaborate with campaign managers, business analysts, and engineering teams to generate measurable business value and inform strategic decisions.

Benefits

• Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being.
• Eligibility for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

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