Head of Data Science, US Card

Capital One; Cambridge (MA); On-site; USD 269,000 - 307,000; Full time

Job summary

Capital One in Cambridge, MA is seeking a Director of Data Science for US Card to lead a data science team that builds and deploys ML models across the credit card lifecycle. You will partner with engineers, product managers, and stakeholders to drive business impact using open-source tools and cloud platforms.

You will mentor teams, champion data-driven decision making, and influence strategy while ensuring high-quality, scalable analytics solutions across marketing, underwriting, and fraud

Qualifications

• Bachelor’s in a quantitative field plus 9 years of analytics experience
• Master’s in a quantitative field or MBA with quantitative concentration plus 7 years analytics experience
• PhD in a quantitative field plus 4 years analytics experience
• At least 4 years using open source languages for large scale data analysis
• At least 4 years working with machine learning
• At least 4 years using relational databases

Responsibilities

• Partner with cross-functional teams to deliver a data-driven product
• Leverage Python, AWS, Spark, and related stack to extract insights from large data sets
• Build ML models through all development phases: design, training, evaluation, validation, implementation
• Translate complex work into tangible business goals

Skills

Open-source languages

Machine learning

Relational databases

Leadership

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

SQL

Job description

Capital One in Cambridge, MA is seeking a Director of Data Science for US Card to lead a data science team that builds and deploys ML models across the credit card lifecycle. You will partner with engineers, product managers, and stakeholders to drive business impact using open-source tools and cloud platforms.

You will mentor teams, champion data-driven decision making, and influence strategy while ensuring high-quality, scalable analytics solutions across marketing, underwriting, and fraud