Director, Global Payments Data Science

Capital One National Association; Chicago, Northern (IL, KY); Hybrid; USD 245,000 - 279,000; Full time

Benefits offered by this job

Health benefits

Incentives & bonus

Job summary

Capital One seeks a Director, Data Scientist for the Global Payment Network. You’ll lead ML initiatives across fraud/risk, merchant acceptance, and payments intelligence, shaping scalable insights from billions of records.

You will partner with data scientists, engineers, and product managers, using Python, AWS, Spark, and H2O to deliver products customers love and translate complex analytics into tangible business impact.

Qualifications

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

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 from large data
• Build machine learning models through all phases of development, from design to deployment
• Translate the complexity of work into tangible business goals

Skills

Python

Conda

AWS

H2O

Spark

Machine learning

Relational databases

Stakeholder communication

Education

Bachelor's degree in a quantitative field

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

PhD in a quantitative field

Tools

SQL

Job description

Capital One seeks a Director, Data Scientist for the Global Payment Network. You’ll lead ML initiatives across fraud/risk, merchant acceptance, and payments intelligence, shaping scalable insights from billions of records.

You will partner with data scientists, engineers, and product managers, using Python, AWS, Spark, and H2O to deliver products customers love and translate complex analytics into tangible business impact.