EXPERIENCE

Principal Associate

TEAM DESCRIPTION

The Business Card & Payments Data Science team builds industry leading machine learning models to power credit underwriting decisions. These models support emerging business card product strategies including risk and spend, and are a key part of our credit infrastructure. This team builds full-spectrum modeling solutions across customer life cycles, engaging in strong collaboration with business stakeholders, product, and software/ML engineering teams, to problem solve and develop innovative approaches that define our long term modeling strategy

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 5 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 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)
• At least 1 year of experience with Python
• At least 1 year of experience with cloud computing
• At least 1 year of experience with machine learning and applied statistics
• 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 3 years’ experience in Python
• At least 2 years’ experience working with cloud computing
• At least 3 years’ experience with machine learning
• At least 3 years’ experience with SQL
• At least 1 year’s experience with model monitoring
  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: $158,600 - $181,000 for Princ Associate, Data Science
  New York, NY: $173,000 - $197,400 for Princ Associate, 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 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).
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  How We Hire
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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!
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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, 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