Director, Data Science - Model Risk

Category

Data Science

Experience

Director

Primary Address

McLean, Virginia

Overview

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 Science Leader 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.

In Capital One’s Model Risk Office, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise. We understand that we can’t prepare for tomorrow by focusing on today, so we invest in the future: investing in new skills, building better tools, and maintaining a network of trusted partners. We learn from past mistakes, and develop increasingly powerful techniques to avoid their repetition.

In this role, you will:

• Partner with a cross-functional team of data scientists, data analysts, and business analysts to drive great decisions through modeling

• Distill the details of complex interconnected modeling systems to influence senior business leaders on model strategy, business use, and risks

• Assess, challenge, and at times defend state-of-the-art decision-making systems to internal and regulatory partners

• Shape our practice of building machine learning models, from design through training, evaluation, validation, and implementation

• Oversee development of benchmark and challenger models to stress test critical modeling decisions

The Ideal Candidate is:

• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo.

• 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 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 obtainingone of the followingwith 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 9 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 7 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) plus 4 years of experience performing data analytics

• At least 4 years of experience leveraging open source programming languages for large scale data analysis

• At least 4 years of experience working with machine learning

• At least 4 years of experience utilizing relational databases

Preferred Qualifications:

• PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics

• At least 5 years of experience in Python, Scala, or R for large scale data analysis

• At least 5 years of experience with machine learning

• At least 1 year of experience working with AWS

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 candidate’s 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 1-800-304-9102 or via email at [email protected]. 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 [email protected]

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).