Manager, Data Science - AI Foundations

About

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 relational databases in 1988. Fast‑forward a few years, and this innovation and our passion for data have propelled us to a Fortune 200 company and a leader in data‑driven decision‑making. As a Data Scientist at Capital One, you’ll be part of a team leading the next wave of disruption at a whole new scale, using the latest computing and machine learning technologies across billions of customer records to unlock opportunities that help everyday people save money, time, and frustration in their financial lives.

Team Description

AI Foundations Specialist Models Data Science team builds and ships state‑of‑the‑art scalable architecture and AI/ML solutions for Capital One’s award‑winning mobile app. We partner with product, tech, and design teams to deliver app features that delight customers with dynamic and personalized experiences, enable them to chat with Capital One’s digital assistant Eno, or search for useful content. You will be the driving force to experiment, innovate, and create next‑generation experiences powered by emerging generative AI technologies.

Responsibilities

• Partner with a cross‑functional team of data scientists, software engineers, machine learning engineers, and product managers to deliver AI‑powered products that change how customers interact with their money.
• Leverage a broad stack of technologies — PyTorch, AWS UltraClusters, Hugging Face, LangChain, Lightning, VectorDBs, and more — to reveal insights hidden within huge volumes of numeric and textual data.
• Serve as the expert in Natural Language Processing (NLP) to harness Large Language Models (LLMs), adapt and fine‑tune them for customer‑facing applications and features.
• Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partner with engineering teams to operationalize them in scalable, resilient production systems that serve 80+ million customers.
• Translate the complexity of your work into tangible business goals using strong interpersonal skills.

Ideal Candidate Traits

• Customer first: Passionate about making the right decisions for customers.
• Innovative: Continuously research and evaluate emerging technologies; stay current on state‑of‑the‑art methods and seek opportunities to apply them.
• Creative: Thrive on defining big, undefined problems, asking questions, and pushing hard to find answers.
• Leader: Challenge conventional thinking, work with stakeholders to improve the status quo, and champion talent development.
• Technical: Comfortable with advanced ML/DL technologies, especially language models; hands‑on experience with LLMs, open‑source tools, and cloud platforms.
• Influential: Communicate clearly to non‑technical audiences and bring cross‑functional teams along on breakthrough innovations.
• Experienced: Background in training language models or large computer‑vision models, with expertise in subdomains such as training optimization, self‑supervised learning, explainability, or RLHF.
• Engineering mindset: Proven track record of delivering models at scale (both training data and inference volumes) and shipping libraries, platforms, or solution‑level code to existing products.

Basic Qualifications

• Bachelor’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) plus 6 years of data analytics experience, or
• Master’s degree in a quantitative field (or MBA with quantitative concentration) plus 4 years of data analytics experience, or
• 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.

Preferred Qualifications

• PhD in a STEM field (Science, Technology, Engineering, or Mathematics).
• Experience working with AWS.
• At least 4 years of experience in Python, Scala, or R.
• At least 4 years of experience with machine learning.
• At least 4 years of experience with SQL.

Compensation (Full‑time Annual Salary)

• McLean, VA: $193,400 – $220,700
• New York, NY: $211,000 – $240,800
• San Jose, CA: $211,000 – $240,800

Compensation varies by location; actual salary will be reflected in the offer letter. This role is also eligible for performance‑based incentive compensation, which may include cash bonuses and/or long‑term incentives.

Benefits

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