Manager, Data Scientist - Optimization

Capital One • McLean, NY

16h

About The Position

Capital One’s Retail Bank modeling and analytics team is focused on defining the next generation of banking through statistical modeling, machine learning, and distributed computing. The team develops data products that enable automation and in-the-moment decision-making. The Manager, Data Scientist - Optimization works across business and technical teams to apply optimization and machine learning to complex business problems and improve decision-making.

The role partners with Product Managers and Business Analysts to design in-market experiments and validate assumptions before full-scale development. It translates ambiguous business challenges into structured mathematical problems, designs and implements optimization models, and develops, tests, and deploys production-grade optimization algorithms and simulation models using Python and commercial or open-source solvers. The role also collaborates with Product, Engineering, and Business teams to integrate optimization engines into software systems and workflows, and builds machine learning models from design through training, evaluation, validation, and implementation.

The ideal candidate has a record of generating strategic business value by optimizing customer experience funnels and risk policies, evaluating external data, and establishing closed-loop experimental frameworks that connect predictive backtesting with live operational outcomes. They are customer-focused, keep up with emerging methods and technologies, and have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

Requirements

• Bachelor’s degree plus 6 years of experience in data analytics, or a master’s degree plus 4 years, or a Ph.D. plus 1 year.
• At least 2 years of experience using open-source programming languages for large-scale data analysis.
• At least 2 years of experience with machine learning.
• At least 2 years of experience with relational databases.
• Hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
• Ability to formulate complex business challenges as mathematical problems and build optimization solutions.
• Experience working cross-functionally to integrate analytical solutions into software systems and workflows.

Nice To Haves

• Ph.D. in a STEM field (Science, Engineering, Operations Research, or Mathematics) plus 2 years of experience in data analytics.
• At least 1 year of experience working with AWS.
• At least 4 years of experience with Python, Scala, or R for large-scale data analysis.
• At least 4 years of experience with machine learning.
• Experience using numerical optimization to solve business problems.
• Experience with linear, non-linear, and integer programming techniques and software packages.
• A track record of optimizing business outcomes and decision systems.
• Experience formulating business problems involving complex data, models, and policy rules.
• Working experience with time-series models.

Responsibilities

• Work with Product Managers and Business Analysts to design in-market experiments and validate assumptions before full-scale development.
• Translate ambiguous business challenges into structured mathematical problems.
• Design and implement linear, mixed-integer, non-linear, and heuristic optimization models to improve decision-making.
• Develop, test, and deploy production-grade optimization algorithms and simulation models using Python and commercial or open-source solvers.
• Partner with Product, Engineering, and Business teams to integrate optimization engines into existing software systems and workflows.
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.
• Optimize customer experience funnels and risk policies, evaluate external data, and establish closed-loop experimental frameworks connecting predictive backtesting with live operational outcomes.
• Research and evaluate emerging technologies and identify opportunities to apply state-of-the-art methods, technologies, and applications.

Benefits

• Comprehensive, competitive, and inclusive 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