Senior Data Scientist - Customer Data Machine Learning Team

Full-time - Mid Level

Mclean, VA

Credit Intermediation and Related Activities

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 Enterprise Consumer Data Science team develops customer matching models that are foundational to servicing our customers and internal data consumers across all Capital One lines of business. The team develops and deploys entity resolution systems operating on massive datasets (hundreds of millions of records) in both batch and realtime, leveraging distributed compute and algorithm optimization to overcome scaling challenges. In this team, you will contribute to the full lifecycle of model development, from scoping business requirements to deployment and monitoring on Capital One's kubernetes platform, and your work will enable a variety of use cases including customer servicing, anti-money laundering, marketing, and bankruptcy processing. Our models are required to make impactful decisions in the face of uncertainty, and we leverage a variety of state-of-the-art interpretable and trustworthy machine learning techniques to support transparency. The team is also heavily invested in expanding core ML technology stack in deep-learning/GenAI and graph analytics and embedding research.

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

Requirements

• Currently has, or is in the process of obtaining a Bachelor's Degree 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
• 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

Nice-to-haves

• Master's Degree in 'STEM' field (Science, Technology, Engineering, or Mathematics), or PhD in 'STEM' field (Science, Technology, Engineering, or Mathematics)
• Experience working with AWS
• At least 2 years' experience in Python, Scala, or R
• At least 2 years' experience with machine learning
• At least 2 years' experience with SQL

Benefits

• Comprehensive health benefits
• Financial benefits
• Inclusive set of benefits that support total well-being