Lead Data Scientist, Applied AI & Generative Systems

Capital One; New York (NY); On-site; USD 177,000 - 201,000; Full time

Job summary

Capital One is seeking a Principal Associate, Data Scientist - Applied AI to drive Generative AI initiatives across vast data and enterprise-scale architectures in New York City. You will partner with data scientists, ML engineers, and product managers to deliver AI solutions that customers love.

The ideal candidate leverages Python and open-source tools, builds multi-agent pipelines, and applies context engineering, fine-tuning, evaluation, and deployment across billions of records to unlock

Qualifications

• Bachelor’s Degree in a quantitative field plus 5 years of data analytics experience
• Master’s Degree in a quantitative field or MBA with quantitative concentration plus 3 years of data analytics experience
• PhD in a quantitative field

Responsibilities

• Partner with a cross-functional team of data scientists, ML engineers, and product managers to deliver Generative AI solutions.
• Leverage a broad stack of technologies—Python, LangChain, AWS, Workflows, and Vector Databases—to build Multi-Agent systems and advanced RAG pipelines.
• Build Generative AI models and pipelines from context engineering through fine-tuning, evaluation, validation, and deployment.
• Translate the complexity of work into tangible business goals.

Skills

Python

LangChain

AWS

Workflows

Vector Databases

Education

Bachelor's degree in quantitative field

Master's degree in quantitative field or MBA with quantitative concentration

PhD in quantitative field

Job description

Capital One is seeking a Principal Associate, Data Scientist - Applied AI to drive Generative AI initiatives across vast data and enterprise-scale architectures in New York City. You will partner with data scientists, ML engineers, and product managers to deliver AI solutions that customers love.

The ideal candidate leverages Python and open-source tools, builds multi-agent pipelines, and applies context engineering, fine-tuning, evaluation, and deployment across billions of records to unlock