Manager, Data Science - US Card - Marketing

Capital One • McLean, VA

3d • Hybrid

About The Position

The Manager, Data Science will work on Capital One’s US Card Marketing Data Science team, which develops machine learning solutions to optimize customer acquisition and deliver personalized customer experiences. The team applies supervised and reinforcement learning to predict customer needs and recommend optimal solutions across marketing channels. Models inform treatment for millions of customers daily and run in analytical and production environments. The work involves custom Python libraries and open-source machine learning tools, in close collaboration with campaign managers, business analysts, and engineering teams to create measurable business value and inform strategic decisions.

The role partners with data scientists, software engineers, and product managers to deliver customer-focused products. It uses technologies including Python, Conda, AWS, H2O, and Spark to analyze large volumes of numeric and textual data, and develops machine learning models throughout their lifecycle—from design and training to evaluation, validation, and implementation. The position is hybrid and follows Capital One’s hybrid policy for required on-site presence at the designated office location.

The ideal candidate is customer-focused, demonstrates leadership and an interest in talent development, and has hands-on experience building data science solutions with open-source tools and cloud platforms. They are statistically minded and experienced in model validation and backtesting, and can retrieve, combine, and analyze data from varied sources and structures.

Requirements

• Currently have, or be in the process of obtaining by the scheduled start date, a bachelor's degree in a quantitative field plus 6 years of data analytics experience; or 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 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, 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.
• Experience developing data science solutions using open-source tools and cloud computing platforms.
• Experience with clustering, classification, sentiment analysis, time series, and deep learning.
• Experience building, validating, and backtesting models, including interpreting confusion matrices and ROC curves.
• Experience retrieving, combining, and analyzing data from a variety of sources and structures.

Responsibilities

• Partner with data scientists, software engineers, and product managers to deliver products customers value.
• Use technologies such as Python, Conda, AWS, H2O, and Spark to identify insights in large volumes of numeric and textual data.
• Build machine learning models through design, training, evaluation, validation, and implementation.
• Translate technical work into tangible business goals.
• Collaborate with campaign managers, business analysts, and engineering teams to ensure models generate measurable business value and inform strategic decisions.
• Develop models that personalize marketing engagement and determine customer treatments at scale.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being.
• 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