Your Team ResponsibilitiesThe Emerging Risks & Opportunities R&D team is building MSCI's next-generation capability for measuring and classifying portfolio exposure to economy-wide structural themes.
Our team develops AI-native research methodologies and data pipelines that enable investors to quantify company and portfolio exposure to emerging risks and opportunities like AI disruption, climate change, geopolitics, and supply chain disruption. Our work centers on researching public and private companies and generating investment signals from diverse data sources including earnings transcripts, company financial filings, and news.
As a senior researcher on the team, you will apply practical expertise in AI agent architecture and knowledge retrieval to solve complex investment research problems. You will contribute to the development of the team's LLM-powered research workflows and help scale research methodologies into investment signals covering public and private companies for institutional investors.
Your Key Responsibilities- Design and develop research methodologies that enable institutional investors to quantify portfolio exposure to economy-wide structural themes, drawing on company financial filings, earnings transcripts, news and press releases, supply chain networks, patent filings, and hiring data in collaboration with investment research experts.
- Implement research methodologies using retrieval-augmented generation (RAG) and agentic pipelines, ensuring transparency for institutional investors.
- Build evaluation pipelines for agentic systems, assess individual pipeline stages for output quality, and design regression tests across prompt and model changes to ensure methodological rigor at scale.
- Work closely with engineering teams to translate research prototypes into scalable, production-ready systems.
- Continuously research and prototype emerging techniques in agentic and reasoning architectures, and develop systematic approaches to codify research methodologies into reusable prompt and taxonomy configurations.
Your skills and experience that will help you excel- Salary range: $130,000 - $180,000 CAD / year plus eligible for annual bonus
- 5+ years of experience building LLM systems for text analysis, information extraction, or document classification, and deep familiarity with knowledge retrieval (RAG) and AI agent architecture.
- Strong Python programming skills with experience in agentic orchestration and LLM application frameworks (e.g. LangGraph, LlamaIndex, or equivalent).
- Demonstrated ability to design prompts and decision rules that translate analytical frameworks into executable LLM pipelines.
- Experience applying AI-driven methodologies to investment research problems, including extracting insights from unstructured data and translating them into measurable, decision-useful signals.
- Track record of building evaluation methodologies for LLM-based systems, including techniques for measuring output quality and consistency at scale across multi-step agentic workflows.
- Comfortable navigating ambiguity and owning research workstreams end-to-end in a fast-paced environment with evolving priorities and iterative prototyping.
