Head of Data Science, Customer & AI Impact (Remote)

Capital One; Lansing (MI); Remote; USD 245,000 - 279,000; Full time

Job summary

Capital One is seeking a Director, Data Science for Consumer and Developer Experience. This remote-eligible role partners with data scientists, engineers, and product managers to deliver data-driven products and insights across billions of records.

You will lead in a cloud-first, open-source environment, leveraging Python, AWS, Spark, and related tools to build and deploy ML solutions while aligning with business goals.

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 analytics experience
• PhD in quantitative field plus 4 years analytics experience
• 4+ years using open source languages for large-scale data analysis
• 4+ years building/deploying AI/ML models in production
• 4+ years designing and analyzing A/B tests

Responsibilities

• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
• Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal insights in large data sets
• Build machine learning models through all phases of development: design, training, evaluation, validation, and implementation
• Translate complex technical work into tangible business goals

Skills

Python

Machine Learning

AWS

Spark

H2O

Conda

Education

Bachelor's degree in quantitative field

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

PhD in quantitative field

Tools

Python

AWS

Spark

H2O

Conda

Job description

Capital One is seeking a Director, Data Science for Consumer and Developer Experience. This remote-eligible role partners with data scientists, engineers, and product managers to deliver data-driven products and insights across billions of records.

You will lead in a cloud-first, open-source environment, leveraging Python, AWS, Spark, and related tools to build and deploy ML solutions while aligning with business goals.