Head of Data Science & AI Strategy

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

Job summary

Capital One is seeking a Director of Data Science to lead end-to-end analytics and ML initiatives across a broad data platform. You will collaborate with data scientists, software engineers, and product managers to deliver impactful solutions on AWS, Spark, and open source tools.

The ideal candidate has extensive experience building production ML models, performing rigorous A/B testing, and guiding teams in a cloud-first environment while aligning technical work with business outcomes.

Qualifications

• Bachelor's Degree in a quantitative field with extensive analytics experience (9 years)
• Master's Degree in quantitative field or MBA with quantitative focus plus 7 years of analytics
• PhD in quantitative field plus 4 years of analytics experience
• 4+ years of experience with open source languages for large-scale data analysis
• 4+ years of experience building/deploying AI/ML models in production
• 4+ years of experience designing and analyzing A/B tests

Responsibilities

• Partner with cross-functional teams to deliver a data-driven product
• Build and deploy ML models through all development stages
• Leverage Python, AWS, Spark, and open-source tools to extract insights from large data
• Translate complex technical work into tangible business goals

Skills

Open source languages

ML in production

A/B testing design

Statistical modeling

Data analysis

Communication

Education

Bachelor's degree in quantitative field

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

PhD in quantitative field

Tools

AWS

H2O

Spark

Python

Conda

Job description

Capital One is seeking a Director of Data Science to lead end-to-end analytics and ML initiatives across a broad data platform. You will collaborate with data scientists, software engineers, and product managers to deliver impactful solutions on AWS, Spark, and open source tools.

The ideal candidate has extensive experience building production ML models, performing rigorous A/B testing, and guiding teams in a cloud-first environment while aligning technical work with business outcomes.