McLean 1 (19050), United States of America, McLean, Virginia

Director, Data Science

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 cloud 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 Consumer Credit Risk Management Modeling & Data, we use multiple cloud-based open-sourced technologies to develop econometric and machine learning models and analytics to predict and generate insight into Capital One's risk and capital needs. We blend cutting-edge quantitative methods with deep understanding of our business, data, and regulatory environment to build predictive models for credit and operational losses, volumes and outstanding balances in support of loss forecasting, CECL/allowance, stress testing, and capital allocation for Capital One. Our models and analyses inform earnings call prep, vertical resilience and downturn preparedness initiatives.

In this role as a Data Scientist Leader in the Consumer Credit Risk Management Organization, you'll lead a team to usher in the next wave of disruption to predictive modeling - using the latest in technology to build & deploy models and solutions leveraging new data sources to provide powerful new insights about our portfolio resilience and opportunities.

On any given day you'll be:

-Evaluating the landscape of tools to understand what will unlock new capabilities and performance and what is just a distraction;

-Leading multiple initiatives involving exploration and analysis of data across a variety of data platforms;

-Motivating and mentoring the Modeling & Data team of data scientists and quantitative modelers to deepen their understanding and use of cutting edge data science and machine learning methods;

-Leveraging extensive, deep technical knowledge and team leadership skills to drive the development of data science solutions and implement data-driven recommendations and outcomes;

-Developing and deploying predictive models to better understand and manage our credit risk and exposure;

-Collaborating with data engineers, data scientists, product managers, and other business analysts to create a nimble and resilient modeling infrastructure that enables CICD;

The Ideal Candidate will be:

-Technical: You have hands-on experience developing data science solutions, from concept to production, and selecting the right tool for the job at hand. You understand modern cloud computing and have a solid foundation in statistics. You have experience prototyping and implementing data science solutions in a financial institution. You know Python, Spark, and/or R.

-A data guru. "Big data" doesn't phase 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.

-Communicator: You can communicate complex ideas clearly. Your team knows their priorities and you manage expectations with your broader cross-functional stakeholder network ad leadership team

-Innovative, but also results-focused. 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.

-Customer & Business-Minded. You have an astute ability to understand the customer and business problem that is to be solved and can drive towards impactful outcomes.

-Leader. You challenge conventional thinking and traditional ways of operating and you work with stakeholders to identify and improve the status quo.

Basic Qualifications:

-Bachelor's Degree plus 9 years of experience in data analytics, or Master's Degree plus 7 years of experience in data analytics, or 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 2 years' experience working with Cloud environments

-At least 1 year experience managing people

-At least 5 years' experience in Python, Scala, R, Spark, or other modern programming language

-At least 7 years' experience with statistics or machine learning

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.