Principal Data Scientist, AI Foundations

Capital One • McLean, NY

2d

About The Position

Capital One’s AI Foundations Specialist Models Data Science team builds and ships scalable architecture and AI/ML solutions for the company’s mobile app. The team partners with product, technology, and design groups to create dynamic, personalized customer experiences, including features for the Eno digital assistant and content search. The Principal Data Scientist will experiment with emerging generative AI technologies to develop next-generation customer experiences.

The role partners with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products. It applies technologies such as PyTorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, and vector databases to analyze large volumes of numeric and textual data. The role focuses on NLP and LLMs, adapting and fine-tuning models for customer-facing applications. Responsibilities span model design, training, evaluation, and validation, as well as working with engineering teams to deploy models in scalable, resilient production systems serving more than 80 million customers. The position also communicates technical work in terms of tangible business goals.

The ideal candidate is customer-focused, innovative, creative, and able to lead and influence cross-functional teams. They stay current with emerging technologies and published methods, bring definition to ambiguous problems, develop talent, and communicate findings to non-technical audiences. They have hands-on experience with LLMs, open-source tools, and cloud platforms; experience training language or large computer vision models; expertise in one or more areas such as training optimization, self-supervised learning, explainability, or RLHF; and an engineering mindset demonstrated by delivering models at scale and libraries, platforms, or solution-level code to existing products.

Capital One will consider sponsoring a new qualified applicant for employment authorization. The role may earn performance-based incentive compensation, including cash bonuses and/or long-term incentives. Capital One offers a comprehensive, competitive, and inclusive benefits package; eligibility varies by employment status and management level. Applications are expected to be accepted for at least five business days.

Requirements

• Bachelor’s degree in a quantitative field plus 5 years of experience performing data analytics; or a master’s degree in a quantitative field or an MBA with a quantitative concentration plus 3 years of experience performing data analytics; or a PhD in a quantitative field. The required degree must be obtained on or before the scheduled start date.
• Hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms.
• Experience training language models or large computer vision models.
• Expertise in one or more key subdomains, such as training optimization, self-supervised learning, explainability, or RLHF.
• Track record of delivering models at scale in training data and inference volumes.
• Experience delivering libraries, platforms, or solution-level code to existing products.
• Ability to collaborate across functions, lead and influence stakeholders, and communicate findings clearly to non-technical audiences.

Nice To Haves

• Master’s degree or PhD in a STEM field.
• Experience working with AWS.
• At least 3 years of experience in Python, Scala, or R.
• At least 3 years of experience with machine learning.
• At least 3 years of experience with SQL.

Responsibilities

• Partner with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products.
• Use a broad technology stack to derive insights from large volumes of numeric and textual data.
• Apply NLP and LLM expertise to adapt and fine-tune models for customer-facing applications and features.
• Build machine learning and NLP models through design, training, evaluation, and validation.
• Partner with engineering teams to operationalize models in scalable, resilient production systems serving more than 80 million customers.
• Translate complex technical work into tangible business goals.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being.
• Eligibility for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal