Director of Data Science - US Card | Lead ML at Scale

ITSMF; McLean (VA); On-site; USD 269,000 - 307,000; Full time

Job summary

Capital One’s US Card Data Science team seeks a Director of Data Science to drive ML strategy and model deployment across the card lifecycle. You will work with engineers, product managers, and analysts to translate complex insights into business actions at scale.

You will lead with a customer-first mindset, applying state-of-the-art methods, and mentoring a team to advance data-driven decision making across marketing, underwriting, and fraud prevention.

Qualifications

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

Responsibilities

• Partner with cross-functional teams to deliver a product customers love.
• Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark to reveal insights from large data.
• Build ML models from design through training, evaluation, validation, and implementation.
• Translate complex work into tangible business goals.

Skills

Python

Conda

AWS

H2O

Spark

Machine learning

Relational databases

Data analytics

Text data analysis

Education

Bachelor's degree in quantitative field

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

PhD in quantitative field

Job description

Capital One’s US Card Data Science team seeks a Director of Data Science to drive ML strategy and model deployment across the card lifecycle. You will work with engineers, product managers, and analysts to translate complex insights into business actions at scale.

You will lead with a customer-first mindset, applying state-of-the-art methods, and mentoring a team to advance data-driven decision making across marketing, underwriting, and fraud prevention.