Senior Associate, Data Scientist - US Card (Applied GenAI)

Senior Associate, Data Scientist - US Card (Applied GenAI) Data is at the center of everything we do. Team Overview The Servicing Intelligence team delivers data science solutions to capture value from unstructured, multi‑modal data sources — text, image, and audio data. The team is an applied data science group building with open source generative AI models and tooling, focusing on application over research to scale the adoption of AI with in‑market solutions. Role Overview As a core member, you will be a driving force to create best‑in‑class products and experiences powered by the latest emerging generative AI technologies. Responsibilities 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 such as LangGraph, LlamaIndex, Weights & 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; partner with engineering teams to operationalize them in scalable and resilient production systems serving 80+ million customers. Assess GenAI or LLM‑powered application architectures in production, including best practices for generative AI development and deployments. Define requirements for AI observability, focusing on 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 non‑deterministic outputs and autonomous actions remain within risk appetite. Guide annotators to curate high‑quality, consistent datasets for model training, evaluation, and ongoing AI monitoring. Collaborate with 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 alignment of data science solutions with business outcomes. Qualifications Currently holds, or is in process of obtaining, 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. Or 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, with the required degree obtained on or before the scheduled start date. Preferred Qualifications Master’s Degree or PhD in a 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 with AI/ML tools and ecosystems such as LangGraph, LlamaIndex, Weights & Biases Weave, PyTorch, or Hugging Face. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. Compensation and Benefits Salary ranges by location: McLean, VA: $135,600 - $154,800; New York, NY: $148,000 - $168,900. This role is eligible for performance‑based incentive compensation, which may include cash bonus(es) and/or long‑term incentives (LTI). Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits supporting total well‑being. Equal Opportunity Employment Capital One is an equal‑opportunity employer (EOE, including disability/veteran). Capital One promotes a drug‑free workplace. Capital One will consider qualified applicants with a criminal history in a manner consistent with applicable laws. For accommodations, please contact CapitalOne Recruiting at View phone number on click.appcast.io or email View email address on click.appcast.io. All information provided will be kept confidential and used only to the extent required to provide needed reasonable accommodations. #J-18808-Ljbffr