5 months ago
Toronto, CanadaMid Level
Responsibilities
- Build production-level AI models and data pipelines that generate transparent, financially material signals for portfolio allocation decisions.
- Apply large language models and NLP techniques to text analysis, document classification, and information extraction.
- Translate ambiguous qualitative concepts into taxonomies, classification schemas, and decision frameworks for systematic model design.
- Design prompts and decision rules that operationalize conceptual frameworks in LLM-based pipelines.
- Collaborate with AI and Engineering teams to convert research prototypes into scalable, operational systems.
- Develop capabilities for measuring and classifying portfolio exposure to emerging risks including AI disruption, climate change, geopolitical risk, supply chain disruption, and demographic shifts.
Requirements
- Bachelor's or Master's degree in Computer Science, Economics, Finance, or another quantitative field, with demonstrated AI/ML expertise.
- At least 3 years of hands-on experience applying large language models and NLP techniques to text analysis, document classification, or information extraction.
- Strong Python programming skills and experience with modern AI frameworks and data processing libraries.
- Experience translating ambiguous concepts into taxonomies, classification schemas, or decision frameworks suitable for systematic model design.
- Demonstrated ability to design prompts and decision rules for LLM-based pipelines.
- Preferred qualifications include familiarity with vector databases, embedding models, semantic search architectures, applied AI research methodologies, agentic workflows, knowledge graphs, and supply chain network analysis.
- Experience with Snowflake, Azure, and production ML deployment is preferred.
Benefits
- Salary range of $101,000 - $140,000 CAD per year plus eligibility for an annual bonus.
- Comprehensive employee benefits and compensation schemes tailored to location.
- Flexible working arrangements and collaborative workspaces.
- Global orientation, access to Learning@MSCI, AI Learning Center, LinkedIn Learning Pro, and tailored learning opportunities.
- Professional growth through multi-directional career paths, internal mobility, and expanded roles.
- Inclusive workplace environment with multiple Employee Resource Groups.
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