Director, Global Payment Data Science

Capital One; Chicago (IL); On-site; USD 210,000 - 239,000; Full time

Job summary

Capital One in Chicago seeks a Director, Data Scientist for the Global Payment Network to lead data science initiatives across payments, fraud, and merchant intelligence with scalable models built on billions of records using open‑source tools and cloud computing.

You will collaborate with data scientists, software engineers, and product managers to deliver a product customers love, exploring Python, AWS, Spark, and H2O to translate data into measurable business impact.

Qualifications

• Bachelor's degree in a quantitative field + 9 years analytics experience.
• Master's degree in quantitative field or MBA with quantitative concentration + 7 years analytics.
• PhD in a quantitative field + 4 years 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 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 — to reveal insights from large data.
• Build machine learning models through all phases of development from design to deployment.
• Translate the complexity of your work into tangible business goals.

Skills

Python

AWS

Machine Learning

Relational Databases

Spark

Scala

R

Team Leadership

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

H2O

Conda

Spark

Job description

Capital One in Chicago seeks a Director, Data Scientist for the Global Payment Network to lead data science initiatives across payments, fraud, and merchant intelligence with scalable models built on billions of records using open‑source tools and cloud computing.

You will collaborate with data scientists, software engineers, and product managers to deliver a product customers love, exploring Python, AWS, Spark, and H2O to translate data into measurable business impact.