Senior Associate, Data Scientist - Nlp

Capital One Capital One · Banking · McLean, VA +2

Senior Associate Data Scientist focused on NLP and LLMs for a financial services company's mobile app. The role involves building, adapting, and fine-tuning LLMs for customer-facing features, operationalizing models in production systems, and leveraging technologies like PyTorch, Hugging Face, LangChain, and VectorDBs. The position requires experience in model development phases from design to validation and operationalization at scale for a large customer base.

What you'd actually do

  1. Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money.
  2. Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
  3. Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features.
  4. 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.
  5. Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

Skills

Required

  • Natural Language Processing (NLP)
  • Large Language Models (LLMs)
  • model development (design, training, evaluation, validation)
  • operationalizing models in production systems
  • Python, Scala, or R
  • machine learning
  • SQL

Nice to have

  • PyTorch
  • AWS
  • Hugging Face
  • LangChain
  • Lightning
  • VectorDBs
  • training optimization
  • self-supervised learning
  • explainability
  • RLHF
  • computer vision models

What the JD emphasized

  • delight customers with dynamic and personalized experiences
  • chat with Capital One’s digital assistant Eno
  • search for useful contents
  • customer facing applications and features
  • serve 80+ million customers
  • training language models or large computer vision models
  • delivering models at scale both in training data and inference volumes
  • delivering libraries, platforms, or solution level code to existing products

Other signals

  • building and shipping state of the art scalable architecture, AI/ML solutions
  • deliver AI powered products
  • adapt and finetune them for customer facing applications and features
  • Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation
  • operationalize them in scalable and resilient production systems that serve 80+ million customers