Senior Data Scientist, Applied AI—Generative AI & RAG

capitalone; Plano (TX); On-site; USD 123,000 - 141,000; Full time

Benefits offered by this job

Health benefits

Performance-based incentives

Competitive compensation

Job summary

Capital One is seeking a Senior Associate Data Scientist to lead applied AI initiatives in financial services. The role emphasizes building generative AI systems, multi‑agent workflows, and large‑scale data pipelines across billions of records.

You will collaborate with data scientists, ML engineers, and product managers to drive business impact. The ideal candidate combines hands-on ML experience with a passion for exploring state‑of‑the‑art methods, and the ability to translate technical work

Qualifications

• Bachelor's or Master's degree in a quantitative field (Statistics, Economics, OR, Analytics, Mathematics, CS) with required experience or MBA with quantitative concentration.
• 2+ years of experience in Python, Scala, or R and machine learning.
• Experience developing data science solutions using open-source tools and cloud computing.

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, PyTorch, LangChain, AWS, Spark, and Vector Databases—to build Multi‑Agent systems and advanced RAG pipelines.
• Build Generative AI models and pipelines through context engineering, fine‑tuning, evaluation, and deployment.
• Translate the complexity of your work into tangible business goals.

Skills

Python

PyTorch

LangChain

AWS

Spark

Vector Databases

NLP

Deep Learning

Education

Bachelor's Degree in a quantitative field

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

Tools

SQL

Scala

R

Job description

Capital One is seeking a Senior Associate Data Scientist to lead applied AI initiatives in financial services. The role emphasizes building generative AI systems, multi‑agent workflows, and large‑scale data pipelines across billions of records.

You will collaborate with data scientists, ML engineers, and product managers to drive business impact. The ideal candidate combines hands-on ML experience with a passion for exploring state‑of‑the‑art methods, and the ability to translate technical work