Principal Associate, Data Science US Card Fraud Authentication Team

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 youll be part of a team thats 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 US Card Fraud Authentication Data Science team operates at the critical intersection of fraud defenses and customer experience. We leverage a modern tech stack - including Python AWS Spark H2O and SQL - to analyze complex datasets and optimize authentication decisioning at Capital One. Our mission is to stay ahead of evolving fraud patterns through a combination of rigorous quantitative analysis and the development of scalable machine learning solutions.

In this role you will:

• Dive into ambiguous fraud landscapes to identify opportunities where machine learning can drive value. You will help design the technical vision for our authentication workflows evaluating feasibility and prototyping innovative ML solutions

• Harness our big data ecosystem (Spark AWS and more) to uncover hidden patterns in massive datasets turning raw information into actionable fraud-prevention strategies

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

• Build machine learning models through all phases of development from design through training evaluation validation and implementation

• Bridge the gap between technical complexity and business strategy articulating the why behind your solutions to influence stakeholders and achieve tangible business goals

The Ideal Candidate is:

• Customer first. You love the process of analyzing and creating but also share our passion to do the right thing. You know at the end of the day its about making the right decision for our customers.

• Creative. You thrive on bringing definition to big undefined problems. You love asking questions and pushing hard to find answers. Youre not afraid to share a new idea.

• Technical. Youre 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. Youve 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 Bachelors Degree in a quantitative field (Statistics Economics Operations Research Analytics Mathematics Computer Science or a related quantitative field) plus 5 years of experience performing data analytics

  • A Masters 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 3 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)

Preferred Qualifications:

• Masters 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 1 year of experience working with AWS

• At least 3 years of experience in Python Scala or R

• At least 3 years of experience with machine learning

• At least 3 years of 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.

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 candidates offer letter.

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.

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- or via email at . 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 Ones recruiting process please send an email to

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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).