Head of Data Science, Global Payments AI Foundations

Capital One; Chicago (IL); On-site; USD 179,000 - 205,000; Full time

Job summary

Capital One in Chicago, IL seeks a Manager Data Science for the Global Network Analytics team. You will lead ML initiatives across billions of network transactions, delivering NLP and LLM-based insights to merchant intelligence and risk decisioning.

Ideal candidates have strong Python/ML experience, hands-on with LLMs, PyTorch, AWS, and vector databases, and a track record delivering scalable models for business impact.

Qualifications

• Bachelor's degree in a quantitative field with analytics experience.
• Masters or PhD with quantitative concentration plus analytics work.
• Experience using open source languages for large-scale data analytics.

Responsibilities

• Partner with data scientists, engineers, and product managers to deliver AI capabilities.
• Leverage PyTorch, AWS, vector databases, and LLMs to extract insights from diverse data.
• Be the NLP/LLM domain expert and deploy models for business users.
• Translate ML complexity into business value and strategic goals.

Skills

Python

Scala

R

Machine Learning

NLP

Education

Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics

Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics

PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics

Tools

PyTorch

AWS

VectorDBs

LLMs

Relational databases

Job description

Capital One in Chicago, IL seeks a Manager Data Science for the Global Network Analytics team. You will lead ML initiatives across billions of network transactions, delivering NLP and LLM-based insights to merchant intelligence and risk decisioning.

Ideal candidates have strong Python/ML experience, hands-on with LLMs, PyTorch, AWS, and vector databases, and a track record delivering scalable models for business impact.