Capital One Logo

Capital One

Manager, Data Science

Posted Yesterday
Be an Early Applicant
Hybrid
McLean, VA
193K-221K Annually
Senior level
Hybrid
McLean, VA
193K-221K Annually
Senior level
Manage a team of data scientists to build machine learning models and improve customer experience while ensuring data security. Collaborate cross-functionally to address fraud threats and enhance financial decision products.
The summary above was generated by AI

Manager, Data Science
Manager , Data Scientist, Retail Bank Data Science
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
The Risk and Resiliency team in the Retail Bank builds the machine learning models that help our customers get an account, bank with the confidence that their accounts are secure, and get access to their money faster. We do data and model pipelining, machine learning, and well-managed model operations using Python, KFP, and ML libraries in our tech stacks.
Role Description
In this role, you will:

  • Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver an experience that helps us book more customers
  • Take a well-managed approach to building customer-facing decision products while also bolstering our defenses with governed vendor tools that fill a niche and complement our own models
  • Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
  • Most critically, build connections with your partners to understand the fraud threats of today and tomorrow so you can devise a modeling roadmap that proxies fraud signal from our data, keeping the fraudsters out while making account opening a seamless experience for others


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 and deploying 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 and an AUPRC view. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.


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 6 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 plus 4 years of experience performing data analytics
    • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics
  • At least 1 year of experience leveraging open source programming languages for large scale data analysis
  • At least 1 year of experience working with machine learning
  • At least 1 year of experience utilizing relational databases


Preferred Qualifications:

  • PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics
  • At least 1 year of experience working with AWS
  • At least 5 years' experience in Python, Scala, or R for large scale data analysis
  • At least 5 years' experience with machine learning
  • At least 5 years' experience with SQL
  • Previous experience with rare event prediction, especially fraud, for credit-like decisions strongly preferred


Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $193,400 - $220,700 for Mgr, Data Science
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
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. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
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. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable 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 [email protected] . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to [email protected]
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Top Skills

AWS
Kfp
Machine Learning
Python
Relational Databases
SQL

Similar Jobs at Capital One

3 Days Ago
Hybrid
2 Locations
193K-241K Annually
Senior level
193K-241K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
The Manager, Data Science role involves partnering with cross-functional teams to deliver customer-focused products, building and evaluating machine learning models, and leveraging technologies to analyze large datasets for insights. The candidate must demonstrate strong technical and interpersonal skills to translate complex data solutions into business goals.
6 Days Ago
Hybrid
4 Locations
176K-241K Annually
Senior level
176K-241K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Manage the Data Science team for Customer Management at Capital One, building machine learning models to enhance customer experience and collaborating with cross-functional teams.
Top Skills: AWSCondaH2OPythonSparkSQL
6 Days Ago
Hybrid
2 Locations
193K-241K Annually
Senior level
193K-241K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Manage a team of data scientists in developing scalable machine learning models and customer data solutions across diverse sectors, leveraging cutting-edge technologies.
Top Skills: AWSCondaH2OPythonSpark

What you need to know about the Los Angeles Tech Scene

Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.

Key Facts About Los Angeles Tech

  • Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
  • Key Industries: Artificial intelligence, adtech, media, software, game development
  • Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
  • Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account