Principal Associate, Data Scientist - Card Intelligence

About the Role

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 relational databases, cutting-edge technology in 1988. Today, this innovation and our passion for data have propelled us to become a Fortune 200 company and a leader in data-driven decision-making. As a Data Scientist at Capital One, you’ll join a team leading the next wave of disruption at scale, using the latest in computing and machine learning technologies across billions of customer records to unlock opportunities that help everyday people save money, time, and stress in their financial lives.

Team Description

The US Card Data Science organization at Capital One leverages our massive wealth of customer data to drive business strategy and deliver world-class customer experiences. Our team builds and deploys sophisticated data science and machine learning models across the entire credit card lifecycle—including marketing, acquisitions, underwriting, and fraud prevention. In this role, you will turn complex insights into real-world impact, shaping financial products that serve and protect millions of cardholders daily.

Responsibilities

• 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 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.

Qualifications

The ideal candidate is:

• Customer-first: You love analyzing and creating but also share our passion for doing the right thing for customers.
• Innovative: You continually research and evaluate emerging technologies, staying current on state-of-the-art methods and seeking opportunities to apply them.
• Creative: You thrive on defining big, undefined problems, asking questions, and pushing hard to find answers. You’re not afraid to share new ideas.
• A leader: You challenge conventional thinking and work with stakeholders to improve the status quo. You’re passionate about talent development for your team and beyond.
• Technical: You’re comfortable with open-source languages and passionate about developing further. You have hands-on experience with data science solutions using open-source tools and cloud computing platforms.
• Statistically-minded: You’ve built, validated, and backtested models. You know how to interpret a confusion matrix or ROC curve and 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, understanding that 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 the 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 field) plus 5 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 field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics.
  • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related field).

Preferred Qualifications

• Master’s Degree in a STEM field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or a PhD in a STEM field.
• At least 1 year of experience working with AWS.
• 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.

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

Pay

The minimum and maximum full-time annual salaries for this role are listed below, by location. Salaries for part-time roles will be prorated based on agreed-upon hours. This role is also eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI).

• Cambridge, MA: $161,800 - $184,600
• McLean, VA: $161,800 - $184,600
• New York, NY: $176,500 - $201,400

Candidates hired to work in other locations will be subject to the pay range associated with that location.

Benefits

Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well-being. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. Learn more at the Capital One Careers website.