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

About the role

The role involves applying expertise in unstructured data (text, image) to harness the power of open source large language models (LLMs) and visual language models (VLMs), leveraging a broad stack of technologies, building machine learning and NLP models, assessing GenAI or LLM-powered application architectures, defining requirements for AI observability, evaluating dynamic behavior of AI systems, guiding annotators to curate high-quality datasets, collaborating on projects with various stakeholders, and ensuring alignment with business outcomes.

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 — 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
• 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 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
• Guide 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
• 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

Qualifications

• Customer first: Passionate about doing the right thing for customers
• Innovative: Continually researching and evaluating emerging technologies
• Creative: Thriving on bringing definition to big, undefined problems
• A leader: Challenging conventional thinking and working with stakeholders to identify and improve the status quo
• Technical: Comfortable with open-source languages and passionate about developing further
• Statistically-minded: Building models, validating them, and backtesting them
• Data guru: Handling retrieval, combination, and analysis of data from various sources and structures

Skills

• Expertise in unstructured data (text, image)
• Leveraging a broad stack of technologies
• Building machine learning and NLP models
• Assessing GenAI or LLM-powered application architectures
• Defining requirements for AI observability
• Evaluating dynamic behavior of AI systems
• Guiding annotators to curate high-quality datasets
• Collaborating on projects with various stakeholders
• Ensuring alignment with business outcomes

Benefits

• Comprehensive, competitive, and inclusive set of health, financial, and other benefits

Pay

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $135,600 - $154,800 for Sr Assoc, Data Science

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website.

Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.

No agencies please.

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

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