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Principal Associate, Data Scientist - AI Software Engineering. 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 AI Foundations – AI Software Engineering Data Science team designs, builds, and delivers state-of-the-art, scalable AI architectures that transform how software is developed at Capital One. We partner closely with product and engineering teams to create multi-agent solutions across the software development lifecycle—including code generation, migration, troubleshooting, root-cause analysis, and documentation—leveraging technologies such as LangGraph, MCP, agent-to-agent protocols, and advanced model customization techniques.
Job Responsibility:
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 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 have:
Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
Experience working with AWS
Experience building production-grade agentic platforms, including RAG and graph-augmented systems, MCP or tool-calling integrations
Demonstrated expertise in advanced model customization techniques—such as fine-tuning, parameter-efficient tuning (LoRA/QLoRA), reinforcement learning, or preference optimization
Prior research and publications in AI/ML conferences
What we offer:
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)