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Capital One

Principal Associate Data Scientist

Capital One, McLean, VA, United States

Principal Associate Data Scientist

Apply locations: McLean, VA; Richmond, VA

Time type: Full time

Posted on: Posted 3 Days Ago

Job requisition id: R202516

Principal Associate, Data Science, Model Risk Office

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:

In Capital One’s Model Risk Office, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise. We understand that we can’t prepare for tomorrow by focusing on today, so we invest in the future: investing in new skills, building better tools, and maintaining a network of trusted partners. We learn from past mistakes and develop increasingly powerful techniques to avoid their repetition.

Role Description:

In this role, you will:

  1. Partner with a cross-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models.
  2. Leverage a broad stack of technologies — Python, Conda, AWS, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
  3. Build machine learning models to challenge “champion models” that are deployed in production today.
  4. Flex your interpersonal skills to present how model risks could impact the business to executives.

The Ideal Candidate is:

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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:

  1. Currently has, or is in the process of obtaining a Bachelor’s Degree plus 4 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 2 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 1 year of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date.
  2. At least 2 years’ experience with machine learning.
  3. At least 2 years’ experience with relational databases.

Preferred Qualifications:

  1. PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics.
  2. At least 1 year of experience working with AWS.
  3. At least 1 year of experience working with Generative AI.
  4. At least 3 years’ experience in Python, Scala, or R for large scale data analysis.
  5. At least 3 years’ experience with machine learning.
  6. At least 3 years’ experience with SQL.
  7. At least 3 years’ experience building or validating models to detect financial crimes (Fraud Detection, Anti-Money Laundering).

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

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website.

This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace.

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