Manager, Data Scientist - Business Cards & Payments

Capital One•McLean, VA

About The Position

Data is at the center of everything we do. As a startup, Capital One disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988. This innovation and passion for data has led Capital One to become a Fortune 200 company and a leader in data-driven decision-making. As a Data Scientist at Capital One, you’ll be part of a team leading the next wave of disruption at a new scale, utilizing the latest in computing and machine learning technologies across billions of customer records to unlock opportunities that help everyday people save money, time and agony in their financial lives. The Business Card & Payments Data Science team builds industry leading machine learning models to power credit underwriting decisions. These models support emerging business card product strategies and are a key part of the credit infrastructure. This team builds full-spectrum modeling solutions across customer life cycles, collaborating with business stakeholders, product, and software/ML engineering teams to problem solve and develop innovative approaches that define long term modeling strategy. 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. You will leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal insights hidden within huge volumes of numeric and textual data. You will build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation, and translate the complexity of your work into tangible business goals.

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 1 year of experience working with AWS
At least 4 years’ experience in Python, Scala, or R for large scale data analysis
At least 4 years’ experience with machine learning
At least 4 years’ experience with SQL

Responsibilities

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