Manager, Data Scientist - US Card DFS Acquisitions

Capital One • McLean, IL

18h • Onsite

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, using the latest in computing and machine learning technologies across billions of customer records to help people save money, time, and agony in their financial lives. The US Card DFS Acquisitions Integration Data Science team builds industry-leading machine learning models to empower core underwriting decisions for new credit card customer acquisitions. The team ensures models meet risk standards, enables COF model use in acquisition area integration policies, supports increased scaling volume by integrating key DFS insights (data, features, or models) into the COF ecosystem, and builds or refits key models combining COF and Discover populations to drive value. The team collaborates closely with cross-functional partners including data engineers, platforms engineers, product managers, credit and business analysts, delivering solutions from ideation to implementation. As model developers, the team owns the full life cycle of models: development, deployment, monitoring, governance, and ongoing usage expansion and releases. They are also creative problem solvers, continuously challenging the status quo and innovating to make models more dynamic, adaptive, robust, and smarter. 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, leverage a broad stack of technologies to reveal insights from data, build machine learning models through all phases of development, 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
• 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 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
• 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 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

Benefits

• comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
• performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Number of Employees: 5,001-10,000 employees