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R184243 Posted 03/25/2024

Principal Associate Data Scientist, AML Modeling and Advanced Data Insights

McLean, Virginia | New York, New York | Chicago, Illinois | Richmond, Virginia
  • Category Data Science
  • Experience Principal Associate
  • Primary Address McLean, Virginia

Overview

Center 3 (19075), United States of America, McLean, Virginia

Principal Associate Data Scientist, AML Modeling and Advanced Data Insights

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 Anti-Money Laundering Modeling and Advanced Data Insights team is on a journey to modernize the way Capital One identifies potential money laundering, terrorist financing, and human trafficking through the use of machine learning, statistics, and other advanced analytic techniques. We develop predictive models, monitoring dashboards, and reporting using tools such as AWS, Snowflake, Python, R, and Spark.  We are continuously expanding our detection capabilities using sophisticated machine learning algorithms by incorporating  supervised and unsupervised learning, graph analytics, NLP, foundation models, etc. to further improve the ability of detecting suspicious activities. As the model development team for advancing transaction monitoring with machine learning, we are responsible for end to end development, deployment, and monitoring of production ML and rules-based models.

Role Description

In this role, you will:

  • 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, SQL  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

  • Use graph databases and algorithms to identify network patterns, detect activities and/or communities of interest, and generate graph features for use in machine learning models

  • 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 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 3 years in data analytics, or currently has, or is in the process of obtaining PhD, with an expectation that required degree will be obtained on or before the scheduled start date

  • At least 1 year of experience in open source programming languages for large scale data analysis

  • At least 1 year of experience with machine learning

  • At least 1 year of experience with relational databases

Preferred Qualifications:

  • Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)

  • At least 2 years of experience in AML modeling or related fields (e.g. Fraud, Risk, CCAR, Liquidity, etc.)

  • At least 1 year of experience working with AWS, Github and version control standards and best practices

  • At least 3 years’ experience in Python

  • 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.

New York City (Hybrid On-Site):$165,100 - $188,500 for Principal Associate, Data Scientist 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 theCapital 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 RecruitingAccommodation@capitalone.com. 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 Careers@capitalone.com

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).

Hiring Process
Stories
Benefits
Career Journey

How We Hire

We take finding great coworkers pretty seriously.

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  • Step 1 Apply

    It only takes a few minutes to complete our application and assessment.

  • Step 2 Screen and Schedule

    If your application is a good match you’ll hear from one of our recruiters to set up a screening interview.

  • Step 3 Interview(s)

    Now’s your chance to learn about the job, show us who you are, share why you would be a great addition to the team and determine if Capital One is the place for you.

  • Step 4 Decision

    The team will discuss — if it’s a good fit for us and you, we’ll make it official!

How to Pick the Perfect Career Opportunity

Overwhelmed by a tough career choice? Read these tips from Devon Rollins, Senior Director of Cyber Intelligence, to help you accept the right offer with confidence.

Your wellbeing is our priority

Our benefits and total compensation package is designed for the whole person. Caring for both you and your family.

  • Illustration of a stethoscope

    Healthy Body, Healthy Mind

    You have options and we have the tools to help you decide which health plans best fit your needs.

  • Illustration of a jar with acorns in it

    Save Money, Make Money

    Secure your present, plan for your future and reduce expenses along the way.

  • Illustration of a mountain peak with a flag

    Time, Family and Advice

    Options for your time, opportunities for your family, and advice along the way. It’s time to BeWell.

Career Journey

Here’s how the team fits together. We’re big on growth and knowing who and how coworkers can best support you.

Visual illustration of a career path at Capital One. Text version included in the Image Description button that follows

A possible career journey at Capital One:

  1. Coordinator
  2. Senior Coordinator
  3. Principal Coordinator
  4. Associate
  5. Senior Associate
  6. Principal Associate
  7. Manager
  8. Senior Manager
  9. Director
  10. Senior Director
  11. VP
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