Lead Data Scientist, Card Finance Innovation & Forecasting

Capital One; McLean (VA); On-site; USD 161,800 - 184,600; Full time

Benefits offered by this job

Health benefits

Performance-based incentives

Sponsorship for employment authority

Job summary

Capital One in McLean, VA is seeking a Principal Associate, Data Scientist for the Card Finance Innovation Team. You will partner with data scientists, engineers, and product managers to elevate forecasting and decision-making across billions of records, delivering models and insights that influence card offers and risk strategies.

You’ll build and productionize ML models using Python, Spark, H2O, Snowflake, and AWS, translating complex data work into clear business impact while guiding

Qualifications

• Bachelor's degree in a quantitative field or higher with data analytics experience.
• 3+ years of experience with Python, Scala, or R.
• 3+ years of machine learning experience.
• 3+ years of SQL experience.
• 1+ year of experience using AWS.

Responsibilities

• Partner with cross-functional data scientists, software engineers, and product managers to deliver a product customers love.
• Leverage Python, Conda, AWS, H2O, Spark, and more to reveal insights hidden within large data sets.
• Build machine learning models through design, training, evaluation, validation, and deployment.
• Translate the complexity of your work into tangible business goals.

Skills

Python

Scala

R

Machine learning

SQL

AWS

Education

Bachelor’s Degree in a quantitative field

Master’s Degree in a quantitative field or MBA with a quantitative concentration

PhD in a quantitative field

Tools

AWS

Spark

H2O

Snowflake

Conda

Job description

Capital One in McLean, VA is seeking a Principal Associate, Data Scientist for the Card Finance Innovation Team. You will partner with data scientists, engineers, and product managers to elevate forecasting and decision-making across billions of records, delivering models and insights that influence card offers and risk strategies.

You’ll build and productionize ML models using Python, Spark, H2O, Snowflake, and AWS, translating complex data work into clear business impact while guiding