Senior Data Scientist, AI Foundations

Capital One • San Jose, CA

22h • $148,000 - $168,900

About The Position

The Senior Data Scientist will join Capital One’s AI Foundations Specialist Models Data Science team, which builds and ships scalable architecture and AI/ML solutions for the company’s mobile app. The team partners with product, technology, and design teams to deliver dynamic, personalized customer experiences, including features for the Eno digital assistant and app search. The role focuses on experimenting with emerging generative AI technologies to create next-generation customer experiences.

The position partners with data scientists, software engineers, machine learning engineers, and product managers to develop AI-powered products. It applies technologies including PyTorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, and vector databases to analyze numeric and textual data. The Senior Data Scientist brings NLP expertise to adapt and fine-tune large language models for customer-facing applications, and develops machine learning and NLP models from design through training, evaluation, and validation. The role also works with engineering teams to operationalize models in scalable, resilient production systems serving more than 80 million customers, and communicates technical work in terms of business goals.

The ideal candidate is customer-focused, innovative, creative, and influential, with leadership and communication skills. They stay current with emerging technologies and state-of-the-art methods, bring definition to complex problems, and help stakeholders improve existing approaches. They have hands-on experience with LLMs, open-source tools, and cloud computing platforms; experience training language models or large computer vision models; expertise in at least one relevant area 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 for existing products.

A quantitative bachelor’s degree plus two years of data analytics experience, a quantitative master’s degree, or an MBA with a quantitative concentration is required. The role may be eligible for employment authorization sponsorship for a qualified applicant. The role is eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

Requirements

• Currently has, or is obtaining by the scheduled start date, a bachelor’s degree in a quantitative field plus two years of data analytics experience, a master’s degree in a quantitative field, or an MBA with a quantitative concentration.
• Experience training language models or large computer vision models.
• Expertise in one or more of training optimization, self-supervised learning, explainability, or RLHF.
• Hands-on experience working with large language models and solutions using open-source tools and cloud computing platforms.
• Engineering mindset and a track record of delivering models at scale in training data and inference volumes.
• Experience delivering libraries, platforms, or solution-level code to existing products.
• Strong communication skills, including the ability to explain findings to non-technical audiences.
• Ability to work across functions and influence teams in AI/ML innovations.

Nice To Haves

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

Responsibilities

• Partner with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products.
• Use technologies such as PyTorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, and vector databases to derive insights from large volumes of numeric and textual data.
• Apply NLP expertise to adapt and fine-tune large language 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.
• Research and evaluate emerging technologies, methods, and applications and identify opportunities to apply them.
• Work with stakeholders to challenge conventional approaches and improve the status quo.
• Communicate findings clearly to non-technical audiences and influence cross-functional teams.
• Deliver models at scale in training data and inference volumes, as well as libraries, platforms, or solution-level code for existing products.

Benefits

• Comprehensive health, financial, and other benefits supporting employee well-being; eligibility varies by employment status and management level.
• Performance-based incentive compensation, potentially including cash bonuses and/or long-term incentives.

What This Job Offers

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