Director, Data Science - Model Risk

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:

1. Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love.
2. 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.
3. Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.
4. Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

The Ideal Candidate is:

1. Innovative. You continually research and evaluate emerging technologies.
2. Creative. You thrive on bringing definition to big, undefined problems.
3. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo.
4. Technical. You're comfortable with open-source languages and are passionate about developing further.
5. Statistically-minded. You've built models, validated them, and backtested them.

Basic Qualifications:

1. 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.
2. At least 4 years of experience in open source programming languages for large scale data analysis.
3. At least 4 years of experience with machine learning.
4. At least 4 years of experience with relational databases.

Preferred Qualifications:

1. PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics.
2. At least 1 year of experience working with AWS.
3. At least 3 years of experience managing people.
4. At least 5 years of experience in Python, Scala, or R for large scale data analysis.
5. 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.

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.