Manager, Data Scientist

The Bank's First Party Fraud (FPF) DS team builds the machine learning (AI/ML) models that enable exceptional customer experiences while protecting the Bank from fraudsters and minimizing operational overhead. Through our models and partnerships, we facilitate customers' fast access to funds, accounts, and overdraft and provide quick resolutions when they face an issue. Simultaneously, we minimize fraud losses in deposits, forgeries, overdraft, claim abuse, and identify theft. This is all done through deploying the latest modeling techniques over complex data and on world-class platforms.

Role Description

In this role, you will:

• Partner with a cross-functional team of data scientists, data analysts, software engineers, business analysts, and product managers to deliver products and services customers love

• Leverage a broad stack of technologies - Python, AWS, graphs, Spark, 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, implementation, and ongoing monitoring

• 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.

• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You thrive on bringing definition to big, undefined problems.

• 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.

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 science

• At least 1 year of experience working with AWS and/or deploying models accessed via API calls

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

• At least 4 years' experience with machine learning with tools like XGBoost and LightGBM

• At least 4 years' experience with SQL

• At least 2 years' experience working with graphs and building GNNs

• At least 2 years' experience developing and deploying with Kubeflow Pipelines (ideal) or other workflow orchestration tools

• Proficiency with the following Python libraries: Polars, DBT, Hydra, and MLFlow

• At least 2 years' experience working in Operations Research or related area, with an ability to build and optimize the policies that turn model scores into customer-impacting decisions. Techniques used may have been integer programming, linear programming, simulated annealing, and/or Bayesian optimization

• Experience deploying a model into a (complex) production environment, ideally having built reusable/modular components along the way

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 (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. 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]

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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).