Capital One
Senior Manager, Data Science - AI Foundations
$230K–$286K
New York, NY +2 · Manager · Full-time · Posted Oct 19, 2026
- Location
- New York, NY
McLean, VA
San Jose, CA - Experience
- Data analytics: 7 years with a Bachelor’s, 5 years with a Master’s or quantitatively concentrated MBA, or 2 years with a PhD. Also, at least 2 years each in large-scale data analysis with open-source programming languages, machine learning, and relational databases.
- Education
- Bachelor’s, Master’s, or PhD in a quantitative field; alternatively, an MBA with a quantitative concentration under the stated experience option. Degree must be held or obtained by the scheduled start date.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Leads development and deployment of scalable NLP and generative AI models and customer-facing features for Capital One’s mobile app and digital experiences.
What you'll do
- Partner with cross-functional teams to build AI-powered customer products.
- Design, train, evaluate, and validate machine learning and NLP models, then partner with engineers to deploy them in production at scale.
- Adapt and fine-tune large language models for customer-facing applications and translate technical findings into business goals.
What they ask for
- At least 2 years of experience using open-source programming languages for large-scale data analysis.
- At least 2 years of experience working with machine learning.
- At least 2 years of experience using relational databases.
- One of the stated quantitative-degree and data-analytics combinations: Bachelor’s plus 7 years, Master’s or quantitatively concentrated MBA plus 5 years, or PhD plus 2 years.
Nice to have
- Experience working with AWS.
- At least 5 years’ experience in Python, Scala, or R; machine learning; or SQL.
Pay
$229,900 - $262,400 USD base salary; $250,800 - $286,200 USD base salary; $250,800 - $286,200 USD base salary
Tools
Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, AWS, SQL
AI focus
Build, train, evaluate, validate, adapt, and fine-tune NLP and large language models for scalable customer-facing generative AI applications and features.
Model-written summary · the original posting is authoritative