Manager, Data Scientist - Upmarket Acquisitions Valuations

Capital One•McLean, VA

2d•$197,300 - $225,100

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. Team Description: The team owns the Upmarket Acquisitions valuations models and plays an integral part in the booking of 3M accounts and granting of $30B in exposure annually in the Acquisitions program. In addition, the team has taken on Valuations for the Discover products booked on the Capital One infrastructure. The Valuations team is comprised of three core pods: Valuations Analytics, Valuations Infrastructure, and Valuations Data Science. The Infrastructure and Data Science pods delve deep into the technical/statistical mechanics of the valuations model, whereas the analytics pod focuses on ensuring the model accurately predicts customer behavior to support rigorous decision-making. The role is on the Valuations Infrastructure pod. To be successful in this role, associates are expected to develop strong knowledge of how the economics of the Upmarket business work and connect that to the underlying code of the valuations model, build a strong understanding of how the models are used by various downstream teams, and develop strong partnerships with the business teams in order to invest in and adjust the model appropriately.

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 6 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 4 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 1 year of experience performing data analytics
At least 1 year of experience leveraging open source programming languages for large scale data analysis
At least 1 year of experience working with machine learning
At least 1 year of experience utilizing relational databases

Nice To Haves

PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics
At least 4 years of experience in Python, Scala, or R for large scale data analysis
At least 4 years of experience with machine learning
At least 4 years of experience with SQL
At least 1 year of experience working with AWS

Responsibilities

Partner with a cross-functional team of business analysts, data scientists, software engineers, and product managers to deliver a product customers love
Leverage a broad stack of technologies - Python, Conda, Sql, 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