Senior Associate, Data Scientist - Applied AI

About the role

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 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.

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, PyTorch, LangChain, AWS, Spark, 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.

Skills

• Innovative: continually researches and evaluates emerging technologies; stays current on published state-of-the-art methods, technologies, and applications and seeks out opportunities to apply them.
• Creative: thrives on bringing definition to big, undefined problems; loves asking questions and pushing hard to find answers; not afraid to share a new idea.
• Technical: comfortable with open-source languages and passionate about developing further; has hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
• Statistically-minded: has built models, validated them, and backtested them; knows how to interpret a confusion matrix or a ROC curve; has experience with clustering, classification, sentiment analysis, time series, and deep learning.

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 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

Qualifications

• Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
• At least 2 years of experience in Python, Scala, or R
• At least 2 years of experience with machine learning
• At least 2 years of experience with SQL
• At least 1 year of experience in AI, Information Retrieval, Deep Learning, or NLP

Pay

• McLean, VA: