Senior Associate, Data Science - Consumer Credit Risk Models and Data

Capital One • McLean, VA

1d • $135,600 - $154,800

About The Position

Capital One’s Consumer Credit Risk Management Models and Data Team develops and deploys predictive models for losses, account volumes, and outstanding balances. These econometric models inform loss allowances, stress testing, capital allocation, earnings calls, recession preparedness, and other strategic decisions. The team combines quantitative methods with knowledge of the business, data, and regulatory environment.

This position focuses on model deployment and platforms. The Senior Associate will help deploy, optimize, and modernize model pipelines and execution platforms, enabling machine learning models to generate insights about the company’s portfolio and growth opportunities. The role partners with data scientists, software engineers, product managers, analysts, and other colleagues in a collaborative environment.

The role uses technologies such as Python, Conda, AWS, and Spark to analyze large volumes of data and develop data science solutions. It covers machine learning model development from design through training, evaluation, validation, and implementation, as well as communicating technical work in terms of business goals.

Requirements

• Currently hold, or be in the process of obtaining by the scheduled start date, a bachelor’s degree in a quantitative field—such as Statistics, Economics, Operations Research, Analytics, Mathematics, or Computer Science—and have 2 years of experience performing data analytics; alternatively, hold or be obtaining a master’s degree in a quantitative field or an MBA with a quantitative concentration.
• Hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
• Ability to retrieve, combine, and analyze data from a variety of sources and structures.
• Experience building, validating, and back-testing models, and interpreting measures such as confusion matrices and ROC curves.
• Statistical knowledge or experience with clustering, classification, sentiment analysis, time series, and deep learning.

Nice To Haves

• Master’s degree in a STEM field or PhD in a STEM field.
• Experience working with AWS.
• At least 2 years of experience with Python, Scala, or R.
• At least 2 years of experience with machine learning.
• At least 2 years of experience with SQL.

Responsibilities

• Partner with data scientists, software engineers, and product managers to deliver a product for customers.
• Use technologies such as Python, Conda, AWS, and Spark to reveal insights in large volumes of data.
• Optimize and deploy machine learning models through design, training, evaluation, validation, and implementation.
• Translate complex technical work into tangible business goals.
• Help deploy, optimize, and modernize model pipelines and execution platforms.

Benefits

• Comprehensive health, financial, and other benefits supporting employee well-being.
• Eligibility to earn performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level