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Manager, Data Science - Fraud, Deep Learning
Manager, Data Science - Fraud, Deep Learning-April 2024
New York
Apr 17, 2025
ABOUT CAPITAL ONE
We’re working on some bold, transformative things—like changing banking for good. What’s in it for you? A career surrounded by brilliant minds. People from different backgrounds, experiences, and educ
10,000+ employees
Consumer Goods & Services, Financial Services
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About Manager, Data Science - Fraud, Deep Learning

  11 West 19th Street (22008), United States of America, New York, New York

  Manager, Data Science - Fraud, Deep Learning

  Manager , Data Scientist, Fraud

  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 Fraud Data Science team builds the machine learning models that help protect our customers and Capital One against fraudsters. We prevent fraud at many steps of a customer journey, from the application to spending and payments, using real-time models. We care very deeply about doing things the right way, automating, and innovating to improve the customer experience and prevent fraud.

  In this role, you will:

  Utilize Deep Learning and Sequence Modelling techniques to build Fraud models

  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, Pytorch, Tensorflow 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.

  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 a Bachelor’s Degree plus 6 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 4 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

  At least 2 years’ experience in open source programming languages for large scale data analysis

  At least 2 years’ experience with machine learning

  At least 2 years’ experience with relational databases

  Preferred Qualifications:

  At least 1 year of experience working with AWS

  At least 2 years’ experience building advanced Deep Learning architectures (for example: RNN’s, CNN’s, Transformers)

  At least 2 years’ experience with Pytorch, Tensorflow or other Deep Learning frameworks

  At least 4 years’ experience in Python, Scala, or R for large scale data analysis

  At least 4 years’ experience with machine learning

  At least 4 years’ experience with SQL

  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.

  New York City (Hybrid On-Site): $201,400 - $229,900 for Mgr, Data Science

  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.

  New York City (Hybrid On-Site): $201,400 - $229,900 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 (https://www.capitalonecareers.com/benefits) . 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).

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