Quant Research Intern: Data, Models & Visualization

Morningstar; Chicago (IL); Hybrid; USD 44,000 - 60,000; Full time

Benefits offered by this job

401(k) match

Comprehensive health benefits

Tuition reimbursement

Job summary

Morningstar is seeking a Quantitative Research Intern in Chicago to contribute to data-driven research and model development. You will clean and organize financial datasets, build visualizations, and shadow analysts to learn how data science informs investment decisions.

Ideal candidates are pursuing a quantitative or financial degree, with Python or R experience, SQL basics, and strong communication skills. Hybrid in-person collaboration is encouraged, with mentorship and hands-on project work.

Qualifications

• Between 0-2 years of professional working experience.
• Currently pursuing a bachelor’s degree in a quantitative or financial discipline (graduating in 2026 or later).
• Familiarity with Python or R for data analysis.
• Basic knowledge of SQL and statistical methods.
• Strong communication skills and ability to explain technical concepts clearly.

Responsibilities

• Assist in cleaning and organizing financial datasets for use in research projects.
• Support the development and testing of models using basic statistical techniques.
• Help build visualizations and summaries to communicate research findings.
• Shadow quantitative analysts to learn how they apply data science to investment questions.
• Collaborate with internal teams to understand how research connects to Morningstar’s products and services.
• Participate in team meetings and contribute ideas to improve research workflows.
• Document processes and findings to support transparency and reproducibility.

Skills

Python

R

SQL

Data visualization

Communication

Education

Bachelor's degree in quantitative or financial discipline

Tools

SQL

Pandas

Job description

Morningstar is seeking a Quantitative Research Intern in Chicago to contribute to data-driven research and model development. You will clean and organize financial datasets, build visualizations, and shadow analysts to learn how data science informs investment decisions.

Ideal candidates are pursuing a quantitative or financial degree, with Python or R experience, SQL basics, and strong communication skills. Hybrid in-person collaboration is encouraged, with mentorship and hands-on project work.