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

Capital One; McLean (VA); On-site; USD 136,000 - 155,000; Full time

Job summary

Capital One in McLean, VA is seeking a Senior Associate Data Scientist for Consumer Credit Risk Models and Data. You will join a team building econometric loss models that inform capital allocation, loss allowances, and stress testing across large datasets.

You will partner with data scientists, engineers and product managers to deploy scalable ML pipelines using Python, AWS, and Spark, translating complex analyses into business impact and protecting customer outcomes.

Qualifications

• Requires a quantitative degree with 2+ years of data analytics experience.
• Experience with statistical modeling and data-driven decision making.

Responsibilities

• Collaborate with data scientists, software engineers, and product managers to deliver valuable solutions.
• Develop and deploy predictive models for losses, accounts, and balances.
• Translate complex analyses into actionable business insights and goals.
• Contribute to model deployment pipelines and platform improvements.

Skills

Python

Machine learning

Statistics

Data analytics

Education

Bachelor’s Degree in a quantitative field

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

Tools

AWS

SQL

Spark

Job description

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

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision‑making.

As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

Have you ever seen the headline in the news “Banks Pass Federal Reserve Stress Tests” and wondered how Capital One determines how much savings (or “capital”) it needs?Or maybe how we analyze the potential impact of the next recession?At the heart of these questions are sophisticated econometric loss models that help us understand the ways in which the economy impacts our loan portfolios and guide strategic decision making at the highest levels of Capital One.

In the Consumer Credit Risk Management Models and Data Team, we blend cutting‑edge quantitative methods, with a deep understanding of our business, data, and regulatory environment to build and deploy predictive models for losses, account volumes and outstanding balances. These models drive key strategic decisions for loss allowances, stress testing, and capital allocation as well as informing our earnings calls and recession preparedness.

If this sounds interesting to you, join us! As a Data Scientist on the deployment & platform side of the team, you’ll be at the forefront helping us to usher in the next wave of disruption by using the latest technology to deploy, optimize and modernize model pipelines and execution platforms that enable machine learning models to provide powerful insights about our portfolio and growth opportunities through new data sources. You will partner with best‑in‑class data scientists, analysts, and engineers to innovate solutions that directly impact the company’s bottom line in a meaningful way. You will do it all in a collaborative environment that values your insight, encourages you to take on new responsibilities, promotes continuous learning, and rewards innovation.

Role Description

• 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 the insights hidden within huge volumes of numeric and textual data
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals

The Ideal Candidate is:

• Innovative. You continually research and evaluate emerging technologies. You stay current on published state‑of‑the‑art methods, technologies, and applications and seek out opportunities to apply them.
• Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
• Technical. You’re comfortable with open‑source languages and are passionate about developing further. You have hands‑on experience developing data science solutions using open‑source tools and cloud computing platforms.
• Statistically‑minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
• A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

Basic Qualifications:

• Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
  • A Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
  • A Master’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration

Preferred Qualifications:

• Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
• Experience working with AWS
• At least 2 years’ experience in Python, Scala, or R
• At least 2 years’ experience with machine learning
• At least 2 years’ experience with SQL

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

Salaries

McLean, VA: $135,600 - $154,800 for Sr Assoc, Data Science

Benefits and Incentives

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long‑term incentives (LTI). Incentives could be discretionary or non‑discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.

This role is expected to accept applications for a minimum of 5 business days.

No agencies please.

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non‑discrimination in compliance with applicable federal, state, and local laws.