Manager, Data Scientist -Advanced Recommenders and Personalization Systems (Transformers, LLMs & Reinforcement Learning)

Capital One; Plano (TX); On-site; USD 179,000 - 205,000; Full time

Job summary

Capital One is seeking a data scientist to design and deploy large-scale recommender systems across digital channels. You will work on transformers, LLMs, and reinforcement learning to personalize experiences for millions of customers, while collaborating with engineering and product teams to deliver production-grade, low-latency solutions.

The role emphasizes data-driven decision making, distributed training, and building evaluation frameworks to prove impact, with competitive benefits and

Qualifications

• Bachelor's degree in a quantitative field plus 6 years of analytics experience.
• Master's degree in a quantitative field or MBA with quantitative concentration plus 4 years analytics.
• PhD in a quantitative field plus 1 year analytics experience.
• At least 1 year of experience leveraging open source 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.

Responsibilities

• Design and develop state‑of‑the‑art recommender systems using transformers, LLMs, and RL.
• Advance personalization through sequence modeling, multi‑modal learning, and contextual decision making.
• Build and fine‑tune foundation models trained on large‑scale customer data.
• Apply reinforcement learning to optimize long‑term user engagement and business outcomes.
• Build evaluation frameworks to measure campaign and system efficacy.
• Collaborate with engineering and product teams to deploy scalable, low‑latency systems.
• Drive innovation in generative recommendations and cross‑domain personalization.

Skills

Python programming

SQL

Machine learning

Deep learning

Recommender systems

Transformers/LLMs

Distributed training

PyTorch

TensorFlow

Big data analytics

Education

Bachelor's degree in quantitative field

Master's degree in quantitative field or MBA with quantitative concentration

PhD in quantitative field

Tools

SQL

AWS

Jupyter/Notebook tooling

Job description

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

We are building the next generation of large-scale reinforcement learning based recommender systems and arbitration engines that will power personalized experiences across marketing, customer servicing, and digital products. This is a high-impact initiative central to our platform, leveraging rich credit and customer behavioral data from tens of millions of customers to deliver intelligent, real-time experiences across our digital experiences, including Mobile, Web, and Email.

Why this role

You’ll help shape a foundational system that reaches a vast portion of the U.S. population, influencing how millions of people discover, decide, and engage across financial and lifestyle experiences.

Role Description

In this role, you will:

• 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 (e.g., contextual Multi-armed Bandits).
• Build and fine‑tune foundation models trained on large-scale customer interaction data.
• Apply reinforcement learning to optimize long‑term user engagement and business outcomes.
• Build state-of-the-art evaluation frameworks to measure the efficacy of our campaigns and recommendation systems.
• Collaborate with engineering and product teams to deploy scalable, production-grade, low‑latency systems.
• Drive innovation in emerging areas such as generative recommendations, conversational systems, and cross‑domain personalization (e.g., travel, shopping).

The Ideal Candidate is

• Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
• Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
• Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
• Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands‑on experience developing data science solutions using open-source tools and cloud computing platforms.
• Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
• A data guru. "Big data" doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.
• 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 (e.g., PyTorch, TensorFlow).
• Ability to translate research into impactful, real‑world systems.

Basic Qualifications

• Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
  • A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics
  • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics
  • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics
• 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

Preferred Qualifications

• PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics
• At least 1 year of experience working with AWS
• At least 4 years’ experience in Python, Scala, or R for large scale data analysis
• At least 4 years’ experience with machine learning
• At least 4 years’ experience with SQL

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

Plano, TX: $179,400 - $204,700 for Mgr, Data Science

New York, NY: $215,200 - $245,600 for Mgr, Data Science

McLean, VA: $197,300 - $225,100 for Mgr, Data Science

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.

Capital One is an equal opportunity employer (EOE, including disability/vet) 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 the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).