Senior Manager, Data Scientist - MS CLIP Valuations

Capital One•Richmond, VA

About The Position

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. The Mainstreet CLIP valuations team builds and manages the models that power one of the largest exposure granting programs in the company. In this role you'll have a unique opportunity to work on the technical side of things while partnering with credit analysts to impact the P&L of Capital One's Mainstreet CLIP platform. This is a chance to be at the forefront of innovation, shaping the next generation of infrastructure and tools that will enable rapid credit decision-making for a business that extends $12+ billion in credit every year.

Requirements

Currently has, or is in the process of obtaining one of the following with 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 7 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 5 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 2 years of experience performing data analytics
At least 2 years of experience leveraging open source programming languages for large scale data analysis
At least 2 years of experience working with machine learning
At least 2 years of experience utilizing relational databases

Nice To Haves

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

Responsibilities

Design and develop a suite of sophisticated credit tools that will be used by a wide range of users, from credit analysts to data scientists.
Leverage your Python skills to create solutions that are both powerful and user-friendly.
Work closely with credit analysts to support and define our credit and lending strategy.
Your work will directly influence the P&L of our largest lending program, giving you a chance to see the tangible results of your efforts on a massive scale.
Interact heavily with both credit analysts and data science partners, translating complex needs into actionable technical solutions.