Senior Data Scientist, Model Risk & Governance

Capital One Group; McLean (VA); Hybrid; USD 162,000 - 185,000; Full time

Job summary

Capital One in McLean, VA is seeking a Principal Associate in Data Science within the Model Risk Office. You will partner with data scientists, software engineers, and product managers to identify model risks and quantify impact across the enterprise.

You will apply Python, SQL, AWS, Spark, and related tools to build and validate models, contribute to governance, and present risk insights to executives.

Qualifications

• Bachelor's degree in a quantitative field with 5+ years analytics experience.
• Master's degree in a quantitative field or MBA with quantitative concentration plus 3 years analytics.
• PhD in a quantitative field.
• At least 1 year of AWS experience.
• At least 3 years’ experience in Python, Scala, or R.
• At least 3 years’ experience with machine learning.
• At least 3 years’ experience with SQL.

Responsibilities

• Partner with a cross-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models.
• Leverage Python, Conda, AWS, Spark, and more to reveal insights from large volumes of data.
• Build machine learning models to challenge champion models deployed in production today.
• Contribute to the model governance framework for the next generation of ML models.
• Present how model risks could impact the business to executives.

Skills

Python

Scala

R

Machine learning

SQL

AWS

Education

Bachelor's degree in quantitative field

Master's degree in quantitative field

PhD in quantitative field

MBA with quantitative concentration

Tools

AWS

Spark

Job description

Capital One in McLean, VA is seeking a Principal Associate in Data Science within the Model Risk Office. You will partner with data scientists, software engineers, and product managers to identify model risks and quantify impact across the enterprise.

You will apply Python, SQL, AWS, Spark, and related tools to build and validate models, contribute to governance, and present risk insights to executives.