Morningstar's Quantitative Research Group is looking to leverage large language models to enhance investment management practices by analyzing massive data sets and distilling complex information into concise and valuable offerings for investors, ultimately driving better outcomes for clients.
Requirements
- Minimum 3 years of hands-on experience implementing AI/machine learning solutions, including RAG, NLP, AI Agents, and transformer models, in commercial applications.
- Expertise in fine-tuning large language models, vector databases, LangChain, LangGraph, Autogen, and prompt engineering.
- Proficiency in Python and SQL, with the ability to write production-quality code deployable on cloud platforms.
- Demonstrated experience in deploying machine learning and deep learning algorithms into production environments.
- Familiarity with Investment Management, particularly Morningstar’s mutual fund, fixed income, and equity databases.
Responsibilities
- Conduct cutting-edge research to develop innovative AI-driven solutions that enhance client outcomes.
- Leverage advanced large language models, including multimodal models and vector embeddings, to continuously improve our AI research assistant.
- Publish research papers, whitepapers, and notebooks focused on optimizing investment workflows for users.
- Identify opportunities to apply AI methodologies to enhance models and products across Morningstar’s diverse datasets and intellectual property spanning multiple asset classes.
- Act as a subject-matter expert, driving the adoption and implementation of AI solutions across Morningstar’s business units.
Other
- Strong communication skills to effectively convey complex technical concepts to non-technical stakeholders.
- Excellent organizational and multitasking skills to manage multiple projects in a fast-paced environment.
- Passion for building AI-driven products and excelling in the Investment Management domain.
- Minimum 3 days onsite in Chicago office.
- Advanced degree (Master’s/PhD preferred) in a quantitative, AI or computational field such as Data Analytics, Computer Science, Machine Learning/AI, Mathematics, Physics, or Statistics.
