Manager, Data Scientist -Advanced Recommenders and Personalization Systems

McLean, VA (onsite) role with Capital One focused on building advanced recommender systems and personalization experiences at scale. You will work on large-scale reinforcement learning approaches to deliver real-time recommendations across customer-facing digital products, powered by transformers, LLMs, and reinforcement learning.

As a Manager, Data Scientist, you will help shape a foundational system designed to influence how millions of people discover, decide, and engage across financial and lifestyle experiences.

What you’ll do

• Design and develop state-of-the-art recommender systems using transformers, large language models (LLMs), and reinforcement learning.
• Advance personalization through sequence modeling, multi-modal learning, and contextual decision-making including contextual Multi-Armed Bandits.
• Build and fine-tune foundation models trained on large-scale customer interaction data.
• Use reinforcement learning to optimize long-term user engagement and business outcomes.
• Create and maintain evaluation frameworks to measure the efficacy of campaigns and recommendation systems.
• Partner with engineering and product teams to deploy scalable, production-grade systems with low latency.
• Drive innovation in areas such as generative recommendations, conversational systems, and cross-domain personalization (for example, travel and shopping).

What you’ll need

• Currently has, or is in the process of obtaining, one of the following (with the expectation the required degree will be obtained on or before the scheduled start date):
  • Bachelor’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) plus 6 years of experience performing data analytics; or
  • Master’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematic
• At least 1 year leveraging open source programming languages for large scale data analysis.
• At least 1 year working with machine learning.
• At least 1 year utilizing relational databases.
• Customer first; innovative and actively researching emerging technologies; creative in bringing definition to ambiguous problems.
• Leadership mindset: challenging conventional thinking and collaborating with stakeholders to improve the status quo.
• Statistically-minded approach, including building models, validating them, and backtesting.
• Strong background in machine learning, deep learning, and recommender systems.
• Hands-on experience with transformers, LLMs, or reinforcement learning.
• Experience working with large-scale datasets and distributed training.
• Solid programming skills in Python and modern ML frameworks (examples include PyTorch and TensorFlow).
• Ability to translate research into impactful, real-world systems.

Preferred qualifications

• 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 in 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.

Technologies you may work with

• Transformers, LLMs, reinforcement learning, sequence modeling, multi-modal learning, contextual Multi-Armed Bandits, foundation models
• Generative recommendations, conversational systems, cross-domain personalization
• Python, PyTorch, TensorFlow, open-source programming languages, relational databases
• AWS, SQL, Scala, R, distributed training

Compensation and benefits

Salary range (McLean, VA): USD 197,300 - 225,100 per year.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits to support your total well-being.

You may also be eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).

About the team

Capital One is building the next generation of large-scale reinforcement learning-based recommender systems and arbitration engines that power personalized experiences across marketing, customer servicing, and digital products.

The initiative leverages credit and customer behavioral data from tens of millions of customers to deliver intelligent, real-time experiences across Mobile, Web, and Email.

Additional notes

• Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
• This role is expected to accept applications for a minimum of 5 business days.
• No agencies please.
• Capital One is an equal opportunity employer committed to non-discrimination in compliance with applicable federal, state, and local laws.
• Capital One promotes a drug-free workplace.
• Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with applicable laws.
• If you need an accommodation, contact Capital One Recruiting at 1-800-304-9102 or [email protected].
• For technical support or questions about Capital One’s recruiting process, email [email protected].
• Capital One does not provide, endorse, or guarantee third-party products, services, educational tools, or other information available through this site.