Director, Data Science - Model Risk

Posted 19 Days Ago
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Chicago, IL
7+ Years Experience
Fintech • Machine Learning • Payments • Software • Financial Services
The Role
Director, Data Science - Model Risk at Capital One. Lead a cross-functional team to deliver customer-centric products using machine learning technologies. Partner with data scientists, software engineers, and product managers to drive business outcomes through data insights. Ideal candidate is innovative, creative, a leader, technically proficient, and statistically-minded.
Summary Generated by Built In

Center 2 (19050), United States of America, McLean, Virginia
Director, Data Science - Model Risk
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
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, 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


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.
  • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.
  • 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 obtaining a Bachelor's Degree plus 9 years of experience in data analytics, or currently has, or is in the process of obtaining a Master's Degree plus 7 years of experience in data analytics, or currently has, or is in the process of obtaining a PhD plus 4 years of experience in data analytics
  • At least 4 years of experience in open source programming languages for large scale data analysis
  • At least 4 years of experience with machine learning
  • At least 4 years of experience with relational databases


Preferred Qualifications:

  • PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
  • At least 1 year of experience working with AWS
  • At least 3 year of experience managing people
  • 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


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, 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 [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).

Top Skills

Python

What the Team is Saying

Ryan Page
Kristen Cornelsen
Natalia Bachmann
The Company
Chicago, IL
55,000 Employees
Hybrid Workplace
Year Founded: 1994

What We Do

At Capital One, we think and work like a tech company, using our digital fluency to transform everything about the customer experience. We’re bending data to our will, and turning a stodgy industry on its head. That’s reflected in our ranking as the number one business technology innovator in the U.S. in the 2016 InformationWeek Elite 100.

Why Work With Us

Here’s another question: What are you looking for? A place where curiosity is the starting point? Where data leads to human insights? Where humanity drives product development? We’re bringing breakthrough products and services to consumers, small businesses, and commercial clients. And each new idea makes life better for millions of people.

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Capital One Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: Not Specified
Chicago, IL

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