Principal Associate, Data Scientist - Applied AI
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 Commercial Bank Applied AI team is at the forefront of embedding Generative AI directly into core business processes. We specialize in building enterprise-grade architectures using advanced techniques such as Multi-Agent Systems, Advanced RAG, Context Engineering, Tool-Calling Frameworks etc. The ideal candidate is deeply passionate about the practical applications of Generative AI and brings hands-on experience in machine learning and AI, gained through either professional industry work or rigorous academic research.
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) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
- At least 2 years of experience in AI, Information Retrieval, Deep Learning or NLP
- At least 3 years of experience in Python, Scala, or R
- At least 3 years of experience with machine learning
- At least 3 years of experience with SQL
Responsibilities
- Partner with a cross-functional team of data scientists, machine learning engineers, and product managers to deliver Generative AI solutions customers love.
- Leverage a broad stack of technologies—Python, LangChain, AWS, Workflows, and Vector Databases—to build Multi-Agent systems and advanced RAG pipelines over vast volumes of numeric and textual data.
- Build Generative AI models and pipelines through all phases of development, from context engineering through fine-tuning, evaluation, validation, and deployment.
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
