Manager, Data Scientist - Card Mainstreet Acquisitions

Capital One • McLean, VA

13d • Onsite

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 Acquisitions team sits at the forefront of technology, model development, and credit strategy innovation at Capital One and is continuously working to innovate ways we handle data, build models, and perform analysis. Positioned at the intersection of model architecture, risk strategy, and emerging AI capabilities, this role serves as the key technical and analytical driver for our multi-model decisioning pipelines and valuations frameworks. We use the latest techniques in machine learning to build predictive models and utilize the advantages of large-scale data and cloud-based processing. Through these techniques, we extract relevant insights from data to tackle a huge variety of business problems, and we partner with credit programs to leverage our insights to improve their customer-facing policies.

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

• Identify, analyze, and mitigate systemic risks within a newly launched, multi-model business decisioning infrastructure through integrated monitoring frameworks
• Identify gaps and vulnerabilities using advanced statistical tools and techniques, leveraging pre-existing infrastructures or building from scratch where necessary
• Build and deploy solutions centered on Large Language Models (LLMs) and Agentic AI
• Partner with cross-functional teams of data scientists, business analysts, and software engineers to deliver on products and tools for the business
• 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