Data Scientist - Machine Learning

114 5th Ave (22114), United States of America, New York, New York

At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding.

Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.

Data Scientist - Machine Learning

At Capital One, data is at the center of everything we do. When we launched 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's Center for Machine Learning, you'll be part of a team that's leading the next wave of disruption using the latest in distributed computing technologies and operating across billions and billions of customer events to unlock the opportunities that help everyday people save money, time and agony in their financial lives.

On any given day you'll be:

  • Using Big Data tools (Hadoop, Spark, Kafka, AWS) to conduct the analysis of billions of customer transaction records in concert with distributed neural network frameworks and other machine learning libraries
  • Writing software to clean and investigate large, messy, structured and unstructured datasets
  • Integrating with external data sources and APIs to discover interesting trends
  • Building machine learning systems from proof of concept through production on clickstream, customer, transaction, or behavioral data (to only name a few!)
  • Creating full data pipelines and novel data tiers for your projects on the road to production
  • Perform internal and external research for publication
  • Contribute to open source projects as part of your job

The Ideal Candidate will be:

  • Curious. You ask why, you explore, you're not afraid to blurt out your disruptive idea. You know Python, Scala, bash, and at least enough Java to be dangerous. You're constantly exploring new open source tools.
  • Wrangler. You know how to programmatically extract data from anything and model it into human-readable deployments.
  • Creative. Big, undefined problems and petabytes of data don't frighten you. You're used to working with abstract data, and you love discovering new narratives in unmined territories.
  • Forward Thinking. You are always reading about the newest research on methods and techniques. You actively try and apply these methods in your own projects, Kaggle Competitions, or in research projects. You actively follow or contribute to open source software implementing these techniques.

Twenty-five years after Capital One was started it's still led by its founder. Be ready to join a community of the smartest people you've ever met, who see the customer first, and want to use their data skills to make a difference.

Basic Qualifications:

  • Bachelor's Degree or military experience
  • At least 1 year experience in open source programming languages for large scale data analysis or simulation
  • At least 1 year experience with machine learning
  • At least 1 year experience with SQL and database structures

Preferred Qualifications:

  • Master's Degree or PhD
  • At least 1 year experience working with AWS
  • At least 2 years' experience in Python, Scala, or Java for large scale data analysis or simulation
  • At least 2 years' experience with machine learning
  • At least 2 years' experience with SQL and other database query paradigms

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


No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at

Meet Some of Capital One's Employees

Ryan P.

Head Of Design

Ryan and his team of designers and developers work at The Shop, a combined technology workshop and retail hub, to create meaningful financial products and services.

Emma S.

Product Manager

On Capital One’s exploratory Research and Development Group, Emma takes consumer-driven products from white space to market with innovative and interactive user-testing lab experiments.

Back to top