Equity Analytics Quant — AI-Driven Research

Morningstar, Inc.; Chicago (IL); On-site; USD 92,000 - 135,000; Full time

Benefits offered by this job

401k match

Life insurance

Health benefits

Disability insurance

Sabbatical

Parental leave

Tuition Reimbursement

Volunteer days

Job summary

Morningstar, Inc. is seeking a Quantitative Analyst to join the Equity Analytics team in Chicago. The role focuses on turning holdings, equity data, and company filings into high-quality analytics, supporting validation of models in production.

You will work independently with senior analysts on judgment calls and priorities. The position emphasizes strong Python/SQL skills and a rigorous, skeptical approach to research across the full research lifecycle.

Qualifications

• Strong foundation in equity fundamentals and valuation.
• Strong Python and SQL skills, data proficiency.
• Rigorous, skeptical research approach from data exploration to validated analysis.

Responsibilities

• Run the full lifecycle of a research task: data gathering, quality assessment, methodology testing, and refinement.
• Build analytics across valuation, business analysis, and equity data under guidance.
• Develop depth in how investors use equity analytics to understand stock exposure within a portfolio.
• Support ongoing model validation from pre-launch checks to production issue resolution.
• Maintain clear, well-documented code and analysis for review and handoff.
• Flag edge cases and data issues to senior analysts when needed.
• Contribute to peer review and stay updated on methodologies and AI-assisted tools.

Skills

Python

SQL

Quantitative research

Job description

Morningstar, Inc. is seeking a Quantitative Analyst to join the Equity Analytics team in Chicago. The role focuses on turning holdings, equity data, and company filings into high-quality analytics, supporting validation of models in production.

You will work independently with senior analysts on judgment calls and priorities. The position emphasizes strong Python/SQL skills and a rigorous, skeptical approach to research across the full research lifecycle.