Data Scientist Lead

JPMorgan Chase JPMorgan Chase · Banking · LONDON, United Kingdom · Asset & Wealth Management

Data Scientist Lead at JPMorgan Chase focusing on designing and implementing ML solutions using LLMs for ESG and Stewardship functions. The role involves content extraction, search, and principal-based reasoning, with a strong emphasis on building evaluation packages and production-quality code. Requires advanced Python, NLP, and LLM expertise, with preferred knowledge in financial markets and ESG.

What you'd actually do

  1. Develop technical solutions utilising LLMs with a focus on problems involving search, content extraction and principal-based reasoning
  2. Build comprehensive evaluation packages to ensure the efficacy and reliability of solutions and to build trust with stakeholders
  3. Collaborate with internal stakeholders to understand business needs, build out requirements, and design technical architectures
  4. Collaborate heavily with engineering functions to deliver high quality, scalable output
  5. Stay up to date with the latest developments in AI and become an SME within the data science function

Skills

Required

  • Advanced degree (MS or PhD) in a quantitative or STEM discipline or significant practical experience in industry.
  • Commercial experience in applying NLP, LLM and ML techniques in solving high-impact business problems, such as semantic search, information extraction, question answering, personalisation, classification, recommendation or forecasting.
  • Advanced python programming skills with experience writing production quality code using ML libraries and deep learning frameworks.
  • Good understanding of the foundational principles and practical implementations of ML algorithms such as clustering, decision trees, deep learning, reinforcement learning, etc.
  • Strong knowledge of NLP, language modelling, prompt engineering, and domain adaptation.
  • Ability to communicate complex concepts and results to both technical and business audiences.

Nice to have

  • Strong analytical skills with an understanding of financial markets and asset management line of business
  • Strong business domain knowledge in ESG, investment stewardship, or buyside investment
  • Familiarity with techniques for model explainability and self-validation
  • CFA or equivalent financial qualification

What the JD emphasized

  • production quality code
  • advanced python programming skills
  • commercial experience in applying NLP, LLM and ML techniques

Other signals

  • LLM solutions for ESG and Stewardship
  • content extraction, search, and principal-based reasoning with LLMs
  • build comprehensive evaluation packages
  • production quality code using ML libraries and deep learning frameworks
  • NLP, language modelling, prompt engineering, and domain adaptation