Principal Associate, Data Scientist - US Card (New To Credit Team)

Principal Associate, Data Scientist - US Card (New To Credit Team)

Join to apply for the Principal Associate, Data Scientist - US Card (New To Credit Team) role at Capital One

Principal Associate, Data Scientist - US Card (New To Credit Team)

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Join to apply for the Principal Associate, Data Scientist - US Card (New To Credit Team) role at Capital One

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 New to Credit Data Science team develops machine learning models for marketing, risk, and valuation. These models help our business partners make informed marketing and underwriting decisions throughout the credit card lifecycle. We prioritize advanced modeling techniques, alternative data sources, and robust infrastructure to enhance decision accuracy and efficiency. Additionally, we conduct thorough statistical analysis to generate insights that influence various business strategies. You will collaborate with data scientists, business analysts, and software engineers on all stages of model development. This work will be conducted in a supportive environment that values your contributions, encourages new responsibilities, promotes ongoing learning, and rewards innovation.
Role Description
In this role, you will:

• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
• Leverage a broad stack of technologies — Python, Conda, AWS, Spark, Kubeflow Pipelines, and more — to reveal the insights hidden within huge volumes of numeric and textual data
• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals
  

The Ideal Candidate is:

• 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.
• 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.
• 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.
• 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 it’s about making the right decision for our customers.
  

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)
  

Preferred Qualifications:

• Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of industry experience in data science, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
• At least 1 year of experience working with AWS
• At least 3 years’ experience in Python
• At least 3 years’ experience with building machine learning models, with at least one year of experience with building GBM models
• At least 3 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.
Chicago, IL: $144,200 - $164,600 for Princ Associate, Data Science
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 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 ; 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 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 One's recruiting process, please send an email to
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).

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

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