Data Science Manager: Lead Production ML at Scale

Capital One National Association; McLean (VA); On-site; USD 197,000 - 225,000; Full time

Job summary

Capital One is seeking a Manager of Data Science to lead data-driven initiatives across the Card DS team. You will build and deploy predictive models using large-scale data, partnering with engineers, PMs, and analysts to deliver products customers love.

You will work with Python, AWS, Spark, and modern ML frameworks, translating complex analyses into clear business outcomes while mentoring others and driving production-ready solutions.

Qualifications

• Bachelor's degree in a quantitative field and 6 years of data analytics experience.
• Master's degree in a quantitative field or MBA with quantitative concentration plus 4 years of analytics experience.
• PhD in a quantitative field plus 1 year of analytics experience.

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 volumes.
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.
• Translate the complexity of your work into tangible business goals for non-technical audiences.

Skills

Data analytics

Machine learning

Communication

Education

Bachelor's Degree in quantitative field

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

PhD in quantitative field

Tools

Python

Conda

AWS

H2O

Spark

SQL

Job description

Capital One is seeking a Manager of Data Science to lead data-driven initiatives across the Card DS team. You will build and deploy predictive models using large-scale data, partnering with engineers, PMs, and analysts to deliver products customers love.

You will work with Python, AWS, Spark, and modern ML frameworks, translating complex analyses into clear business outcomes while mentoring others and driving production-ready solutions.