Data Scientist [multiple Positions Available]

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Asset & Wealth Management

Develops and deploys LLM-based solutions for NLP tasks in a financial context, including extraction, search, reasoning, and recommendation. Focuses on prompt engineering, RAG, tool calling, and agent orchestration, with an emphasis on evaluating and monitoring model performance.

What you'd actually do

  1. Study, design, and develop deep learning frameworks for NLP tasks aligned with business requirements.
  2. Develop technical solutions utilizing large language models for a variety of problems including content extraction, search and question answering, reasoning and recommendation.
  3. Build testing setups to evaluate model performances and ensure the efficacy and reliability of the LLM solutions.
  4. Monitor and improve model performance through feedback and active learning.
  5. Collaborate with engineering and product teams to deploy scalable solutions in production.

Skills

Required

  • Python
  • Java
  • Torch
  • Huggingface
  • prompt engineering
  • retrieval augmented generation (RAG)
  • tool calling
  • agent orchestration
  • NLP

Nice to have

  • deep learning frameworks
  • content extraction
  • search
  • question answering
  • reasoning
  • recommendation
  • financial markets

What the JD emphasized

  • Designing AI/ML models for Natural Language Processing (NLP) solutions
  • Building LLM-based solutions including prompt and context engineering, retrieval augmented generation (RAG), tool calling and agent orchestration
  • Analyzing financial reports, analysts notes, client communications to extract actionable insights and empower data-driven decision making in financial markets

Other signals

  • LLM solutions
  • NLP tasks
  • deep learning frameworks