Senior Quant: Risk Analytics & AI Lead

Morningstar, Inc.; Chicago (IL); Hybrid; USD 118,000 - 172,000; Full time

Benefits offered by this job

401k match up to 6%

Stock ownership

Company-provided life insurance

Health benefits (medical/dental/vision

Sabbatical leave

Tuition reimbursement

Parental leave

Volunteer days

Job summary

Morningstar, Inc. seeks a Senior Quantitative Analyst to join the Quantitative Research team and advance the Morningstar Risk analytics platform.

You will analyze large financial datasets across asset classes, own projects from framing through production, and collaborate with product and engineering to deliver actionable insights. Ideal candidates have a strong foundation in statistics/econometrics, experience with Python/SQL, and familiarity with AWS tools (S3/EMR/Athena).

Qualifications

• Bachelor's degree with 5 years of experience, or master's with 3 years in quantitative research or financial data.
• Strong investing knowledge and financial markets understanding.
• Solid statistics/econometrics applied to finance.
• Proficiency in Python and SQL with production-quality code.

Responsibilities

• Develop understanding of Morningstar methodologies and risk analytics products.
• Collaborate with analysts and engineers to implement methodologies.
• Become SME on fixed income, equity, and mutual funds.
• Understand Morningstar data systems and support model validation.
• Own projects end to end from scoping to production handoff.
• Communicate progress, risk, and trade-offs with product and engineering teams.

Skills

Python

SQL

AWS

Data analysis

CFA charter

Education

Bachelor's degree in a related field

Tools

S3

EMR

Athena

Job description

Morningstar, Inc. seeks a Senior Quantitative Analyst to join the Quantitative Research team and advance the Morningstar Risk analytics platform.

You will analyze large financial datasets across asset classes, own projects from framing through production, and collaborate with product and engineering to deliver actionable insights. Ideal candidates have a strong foundation in statistics/econometrics, experience with Python/SQL, and familiarity with AWS tools (S3/EMR/Athena).