Data Scientist developing and implementing LLM - based agents and leveraging AI techniques to improve client value. Collaborating on project challenges in a dynamic, start - up environment at Gartner.
About the role
- Senior Associate Data Scientist at Capital One applying AI on large datasets for decision-making and customer engagement. Collaborating with teams to build innovative AI-driven solutions.
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.
- 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
- A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)
- 2 years of experience performing data analytics
- 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.
Benefits
- comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
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