Senior Associate, Generative AI Data Scientist

Capital One National Association; Plano (TX); On-site; USD 123,000 - 141,000; Full time

Job summary

Capital One is seeking a Senior Associate, Data Scientist - Applied AI (Financial Services) to lead Generative AI initiatives across billions of records. You will partner with data scientists, ML engineers, and product managers to deliver practical AI solutions that drive real business value.

You will develop end-to-end AI pipelines using Python, PyTorch, LangChain, AWS, Spark, and vector databases, from context engineering and fine-tuning to evaluation and deployment, translating technical

Qualifications

• Bachelor's Degree in a quantitative field plus 2 years of data analytics experience.
• Master's Degree in a quantitative field or an MBA with a quantitative concentration.

Responsibilities

• Partner with a cross-functional team of data scientists, ML engineers, and product managers to deliver Generative AI solutions customers love.
• Leverage a broad stack of technologies—Python, PyTorch, LangChain, AWS, Spark, and Vector Databases—to build Multi‑Agent systems and advanced RAG pipelines over vast volumes of numeric and textual data.
• Build Generative AI models and pipelines through all phases of development, from context engineering through fine‑tuning, evaluation, validation, and deployment.
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

Skills

Python

PyTorch

LangChain

AWS

Spark

Vector Databases

SQL

Education

Bachelor's Degree in a quantitative field

Master's Degree in a quantitative field or MBA with a quantitative concentration

Job description

Capital One is seeking a Senior Associate, Data Scientist - Applied AI (Financial Services) to lead Generative AI initiatives across billions of records. You will partner with data scientists, ML engineers, and product managers to deliver practical AI solutions that drive real business value.

You will develop end-to-end AI pipelines using Python, PyTorch, LangChain, AWS, Spark, and vector databases, from context engineering and fine-tuning to evaluation and deployment, translating technical