Location: all cities,VA, USA
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.
Role Description
The risk R&D team sits in the Card DS Partnerships team is focusing on developing a prototype for next-generation Card risk models, designed to capture emerging risks more quickly and accurately, for all card products. Our efforts will extend beyond innovating model structures; We will also invest in infrastructure tools that systematize the development process of Card models. The team is focusing on creating high-impact models that enhance business performance while also maintaining a healthy work-life balance. We place a high value on the professional development of our associates, encouraging and requiring the adoption of cutting-edge technologies to innovate our model development processes. If you are detail-oriented, passionate about learning and applying new machine learning techniques to drive business improvements, skilled in coding, an effective communicator, and an excellent team player, we invite you to join our team.
In this role, you will:
The Ideal Candidate is:
Basic Qualifications:
Preferred Qualifications:
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.
New York City (Hybrid On-site): $165,100 - $188,500 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 will consider sponsoring a new qualified applicant for employment authorization for this position.
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 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.
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