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Senior Associate, Data ScientistCapital One National Association • Virginia, Minnesota, United States
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Senior Associate, Data Scientist

Capital One National Association
  • US
    Virginia, Minnesota, United States
  • US
    Virginia, Minnesota, United States
Postuler Maintenant

À propos

Senior Associate, Data Scientist 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 on 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 Credit Risk Management, Loss Forecasting and Allowance team uses the latest technologies and innovative models and data to forecast and optimize future losses associated with Capital One’s credit card portfolio. We partner with model development and software engineering teams to build predictive models and automate insight generation.
As a Data Scientist, you will focus on loss forecasting modernization and data transformation. The qualified candidate will support card loss forecasting: resilience, outlook, allowance and CCAR.
Role Description In this role, you will:
Partner with a cross‑functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models.
Leverage a broad stack of technologies—Python, Conda, AWS, Spark, and more—to reveal the insights hidden within data.
Build statistical/machine learning models to challenge “champion models” that are deployed in production today.
Contribute to the model governance of the next generation of machine learning models.
Flex your interpersonal skills to present how model risks could impact the business to executives.
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.
Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
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 have experience with a wide array of methods.
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 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 2 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.
Preferred Qualifications:
Master’s Degree in STEM (Science, Technology, Engineering, or Mathematics), or PhD in STEM (Science, Technology, Engineering, or Mathematics).
Experience working with AWS.
At least 2 years’ experience in Python, Scala, or R.
At least 2 years’ experience with machine learning.
At least 2 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.
McLean, VA: $135,600 - $154,800 for Sr Assoc, Data Science.
Richmond, VA: $123,300 - $140,700 for Sr Assoc, 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.
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; SanFrancisco, California Police Code Article 49, Sections4901‑4920; 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.
For technical support or questions about Capital One’s recruiting process, send an email to Careers@capitalone.com.
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  • Virginia, Minnesota, United States

Compétences linguistiques

  • English
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