Director, Data Science — Remote AI Leader

Capital One; Chicago (IL); Remote; USD 245,000 - 279,000; Full time

Job summary

Capital One is seeking a data science leader to partner with cross-functional teams to deliver data-driven products. You will build and deploy ML models using Python, Spark, AWS, and open-source tools, turning complex data into actionable business insights.

The role emphasizes designing and validating models, running A/B tests, and aligning technical work with business goals, with opportunities to influence customer outcomes in a data-first organization.

Qualifications

• Bachelor's degree in a quantitative field plus 9 years of analytics experience
• Master's degree in a quantitative field or MBA with quantitative concentration plus 7 years of analytics experience
• PhD in a quantitative field plus 4 years of analytics experience
• At least 4 years of experience with open source programming languages for large-scale data analysis
• At least 4 years of experience building/deploying AI/ML models in production
• At least 4 years of experience designing and analyzing A/B tests

Responsibilities

• Partner with a cross-functional team to deliver a product customers love
• Leverage a broad stack of technologies (Python, Conda, AWS, Spark, and more) to reveal insights from large data
• Build machine learning models through all development phases from design to deployment
• Translate complex work into tangible business goals

Skills

Open source languages

Production ML models

A/B testing

Data analysis

Education

Bachelor's in quantitative field

Master's in quantitative field or MBA with quantitative concentration

PhD in quantitative field

Tools

AWS

Spark

H2O

Conda

Job description

Capital One is seeking a data science leader to partner with cross-functional teams to deliver data-driven products. You will build and deploy ML models using Python, Spark, AWS, and open-source tools, turning complex data into actionable business insights.

The role emphasizes designing and validating models, running A/B tests, and aligning technical work with business goals, with opportunities to influence customer outcomes in a data-first organization.