Data Science Lead, Card Fraud Prevention

Capital One Group; New York (NY); On-site; USD 251,000 - 286,000; Full time

Job summary

Capital One is recruiting a Senior Manager, Data Scientist for Card Fraud Prevention in New York, NY. This role leads data science initiatives that detect and mitigate fraud using machine learning at scale.

You will collaborate with engineers, product managers, and data scientists to deliver production-ready models and insights. The ideal candidate combines strong leadership with hands-on expertise in Python, ML, AWS, and modern big data tools, driving impactful fraud prevention solutions for

Qualifications

• Bachelor's degree in a quantitative field plus 7+ years of data analytics experience
• Master's degree in quantitative field or MBA with quantitative concentration plus 5+ years of data analytics experience
• PhD in quantitative field plus 2+ years of data analytics experience
• 2+ years of experience with open source languages for large-scale data analysis
• 2+ years of experience with machine learning
• 2+ years of experience using relational databases

Responsibilities

• Partner with cross-functional teams to deliver data science products loved by customers
• Leverage Python, AWS, Spark, H2O, and other tools to analyze large text and numeric datasets
• Build machine learning models through all development phases: design, training, evaluation, validation, implementation
• Translate complex work into tangible business goals for stakeholders

Skills

Python

Spark

Machine learning

Relational databases

Education

Bachelor's degree in quantitative field

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

PhD in STEM field

Tools

AWS

H2O

PyTorch

Kubernetes

Ray

Conda

Job description

Capital One is recruiting a Senior Manager, Data Scientist for Card Fraud Prevention in New York, NY. This role leads data science initiatives that detect and mitigate fraud using machine learning at scale.

You will collaborate with engineers, product managers, and data scientists to deliver production-ready models and insights. The ideal candidate combines strong leadership with hands-on expertise in Python, ML, AWS, and modern big data tools, driving impactful fraud prevention solutions for