This role provides an exciting opportunity to make a real impact in the asset management industry, work with cutting-edge technologies, and continuously learn and experiment with the latest data science and AI/LLM techniques.

As an Associate in the NLP/LLM Data Scientist Team within Asset Management, you will be at the forefront of enhancing and facilitating various steps in our investment process. You’ll apply cutting-edge data science and machine learning—especially NLP and LLMs—to reengineer processes, improve operational efficiency, and enhance client and investor experiences. You’ll work closely with business stakeholders, technologists, and control partners to design, deliver, and operate solutions in production at scale.

Job Responsibilities

• Collaborate with internal stakeholders to identify business needs and develop NLP/ML solutions that address client needs and drive transformation.
• Apply large language models (LLMs), machine learning (ML), and statistical methods to improve decision-making and streamline workflows.
• Design and build agentic frameworks for LLM-based systems, including multi-step orchestration, tool use, and workflow policies that align with business controls and SLAs.
• Collect, curate, and document datasets for model training and evaluation with strong data governance.
• Monitor and improve model performance through feedback and active learning.
• Collaborate with technology teams to deploy and scale the developed models in production.
• Deliver written, visual, and oral presentation of modeling results to business and technical stakeholders.
• Stay up-to-date with the latest research in LLM, ML and data science. Identify and leverage emerging techniques to drive ongoing enhancement.

Required qualifications, capabilities, and skills

• Advanced degree (MS or PhD) in a quantitative or technical discipline or significant practical experience in industry.
• Minimum of 3 years of experience in applying NLP, LLM and ML techniques in solving high-impact business problems, such as semantic search, information extraction, question answering, workflow automation.
• Demonstrated experience designing and building RAG, MCP tools and LLM agent systems (e.g., tool-enabled reasoning, multi-step workflows, retrieval and planning).
• Proven experience deploying and operating AI/LLM models in production.
• Advanced Python programming skills with production‑quality coding; familiarity with the latest developments in LLM.
• Strong knowledge of language models, prompt engineering, model finetuning, and domain adaptation.
• Ability to communicate complex concepts and results to both technical and business audiences.

Preferred qualifications, capabilities, and skills

• Prior experience in an Asset Management line of business, especially Operations
• Familiarity with LLM/AI model guardrails and observability practices (e.g., evaluation frameworks, bias/hallucination checks).
• CFA designation or current pursuit of the CFA is preferred.