Data Science Manager, Global Payments AI Foundations

Capital One; Deerfield (IL); On-site; USD 179,000 - 246,000; Full time

Benefits offered by this job

Performance-based incentives

Comprehensive benefits

Job summary

Capital One is hiring a Data Scientist to join the Global Network Analytics team, building ML engines and AI tools to power merchant intelligence, fraud/risk decisioning, and automation at scale.

You will collaborate with data scientists, software engineers, ML engineers, and product managers, using PyTorch, AWS, VectorDBs, and LLMs to turn complex data into actionable business insights and support enterprise AI initiatives.

Qualifications

• Bachelor's degree in a quantitative field plus 6 years of data analytics experience
• Master's degree in quantitative field or MBA with quantitative concentration plus 4 years of data analytics experience
• PhD in quantitative field plus 1 year of data analytics experience
• At least 1 year of experience leveraging open source programming languages for large scale data analysis
• At least 1 year of experience with machine learning
• At least 1 year of experience utilizing relational databases

Responsibilities

• Partner with cross-functional teams to deliver AI-powered capabilities evaluating billions of network transactions
• Leverage PyTorch, AWS, VectorDBs, and LLMs to extract insights from complex data feeds
• Serve as NLP and LLM domain expert and deploy these technologies for business users
• Translate ML complexity into tangible business value and strategic goals

Skills

Python

Scala

R

SQL

LLMs

Embedding models

Vector databases

NLP

Education

Bachelor's degree in quantitative field

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

PhD in quantitative field

Tools

PyTorch

AWS

VectorDBs

Job description

Capital One is hiring a Data Scientist to join the Global Network Analytics team, building ML engines and AI tools to power merchant intelligence, fraud/risk decisioning, and automation at scale.

You will collaborate with data scientists, software engineers, ML engineers, and product managers, using PyTorch, AWS, VectorDBs, and LLMs to turn complex data into actionable business insights and support enterprise AI initiatives.