Senior Associate, Data Scientist – US Card, Applied GenAI

Role Overview

• Apply expertise in unstructured data (text, image) to harness the power of open source large language models (LLMs) and visual language models (VLMs)
• Leverage a broad stack of technologies — LangGraph, LlamaIndex, Weights and Biases Weave, Hugging Face, PyTorch, AWS, and more — to automate workflows using huge volumes of text and vision data
• Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers. Assessing GenAI or LLM-Powered application architectures in production, including best practices for Generative AI development and deployments.
• Define requirements for AI observability, focusing on the traceability of autonomous decisions and comprehensive system audit trails. Evaluate the dynamic behavior of AI systems and oversee the development of key continuous monitoring controls and testing, ensuring that non-deterministic outputs and autonomous actions remain within risk appetite.
• Get into the weeds of internal business processes and data operations by guiding annotators to curate high quality, consistent datasets for model training, evaluation, and ongoing AI monitoring.
• Collaborate on a team of data scientists through all phases of project development, from design through training, evaluation, validation, implementation, and maintenance. Interact with a variety of internal stakeholders to ensure the alignment of data science solutions with business outcomes.

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
• 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
• At least 2 years’ experience AI/ML tools and ecosystems, such as LangGraph, LlamaIndex, Weights and Biases Weave, Pytorch, or Hugging Face.

Tech Stack

• AWS
• Open Source
• Python
• PyTorch
• Scala
• SQL

Benefits

• Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.