Principal Data Scientist - AI Foundations, Specialist Models
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 Entity Resolution Systems team builds and ships state of the art machine learning solutions to support entity resolution within the enterprise. A core capability that powers a wide range of use cases spanning from marketing to customer servicing, our work has immediate impact across multiple lines of business. We partner with product, tech and design teams to deliver personalized experiences to our data and platform users to drive productivity and innovation. You will be the driving force to experiment, innovate and create next generation experiences powered by the latest emerging ML technologies and turbo-charged thru agentic software development practices. We are building a modern, extensible entity resolution stack that leverages the latest developments in deep learning and transformer architectures, graph approaches. On this team, team members apply the latest research and methodologies to real-world problems and deliver solutions at scale for our 100M+ customers.
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 5 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 3 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)
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 3 years’ experience in Python, Scala, or R
- At least 3 years’ experience with machine learning
- At least 3 years’ experience with SQL
Responsibilities
- Partner with a cross-functional team of data scientists, software engineers, and product managers to build a next-generation entity resolution solution that leverages cutting-edge machine learning approaches to solve real-world business problems
- Leverage a broad stack of technologies — Python, AWS, Spark, modern state of the art models like transformers, graph ML, 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
- Leverage Agentic AI tools and workflows to build and test
- Flex your interpersonal skills to translate the complexity of your work into tangible business goals
Benefits
- performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
- comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
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What This Job Offers
Job Type
Full-time
Career Level
Principal
