Manager, Data Science - AI Foundations

Capital One • McLean, NY

2d • $197,300 - $245,600

About The Position

The Manager, Data Science, AI Foundations role is part of 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 to create dynamic, personalized customer experiences, including features for Capital One’s digital assistant, Eno, and search.

The role leads experimentation and innovation in generative AI. Working with data scientists, software engineers, machine learning engineers, and product managers, the manager develops AI-powered products and uses technologies such as PyTorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, and vector databases. The role applies NLP and large language models to customer-facing applications, builds models through design, training, evaluation, and validation, and partners with engineering teams to deploy them in scalable, resilient production systems. The role also translates technical work into business goals and contributes to talent development and cross-functional innovation.

Capital One lists a minimum and maximum full-time annual salary of $197,300–$225,100 in McLean, Virginia, and $215,200–$245,600 in New York, New York, and San Jose, California. The role is eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives. Capital One describes its benefits as a comprehensive, competitive, and inclusive set of health, financial, and other benefits; eligibility varies by employment and management status.

Requirements

• A bachelor's degree in a quantitative field plus 6 years of experience performing data analytics; or a master's degree in a quantitative field or an MBA with a quantitative concentration plus 4 years of data analytics experience; or a PhD in a quantitative field plus 1 year of data analytics experience. The required degree may be in progress if it is expected to be obtained on or before the scheduled start date.
• 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.
• Hands-on experience with large language models and solutions using open-source tools and cloud computing platforms.
• Experience training language models or large computer vision models, with expertise in at least one relevant subdomain such as training optimization, self-supervised learning, explainability, or RLHF.
• An engineering mindset and a track record of delivering models at scale in training data and inference volumes.
• Ability to communicate clearly and effectively with non-technical audiences and influence cross-functional teams.

Nice To Haves

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

Responsibilities

• Partner with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products.
• Experiment, innovate, and create customer experiences powered by emerging generative AI technologies.
• Use technologies such as PyTorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, and vector databases to analyze numeric and textual data.
• Apply NLP and large language models to customer-facing applications, adapting and fine-tuning models for product 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.
• Translate technical work into tangible business goals and communicate findings to non-technical audiences.
• Research and evaluate emerging technologies and identify opportunities to apply state-of-the-art methods.
• Challenge conventional thinking, collaborate with stakeholders to improve existing approaches, and support talent development for the team and beyond.
• Help drive cross-functional innovation and deliver models, libraries, platforms, or solution-level code for existing products.

Benefits

• Comprehensive, competitive, and inclusive health, financial, and other benefits; eligibility varies by full-time or part-time status, exempt or non-exempt 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: Manager