Undergraduate Intern – Quantitative Data & Finance
Employment type
Full-time
Work setting
On-site
Location
Cambridge, MA
Schedule
Day shift
Posted
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Job overview
The Undergraduate Intern – Quantitative Data & Finance role is onsite in Cambridge, MA; compensation is not specified. The internship supports the company’s Finance and IT teams with data analysis and quantitative problem-solving. The intern works with financial and operational datasets to organize and validate information, build spreadsheets and simple models, and support reports and visualizations. The work applies quantitative coursework to practical business problems and supports data-driven decision-making.
What you'll do
- Organize, clean, and validate structured data
- build and maintain Excel spreadsheets and simple analytical models
- support reports, dashboards, and visualizations
- identify data patterns, inconsistencies, and trends
- assist with automation or efficiency improvements using Excel, SQL, or Python where applicable
- collaborate on data, finance, and technology tasks.
What we're looking for
- Skills & competencies
- undergraduate internquantitative datafinancedata analysisexcelfinancial datasetsmodelingdashboardscambridge masummer 2026possible extension
- Work arrangement
- Weekend coverage required
Benefits & perks
- Hands-on experience with financial data and analytics workflows
- mentorship and professional development
- opportunity to build data and modeling skills.
Why this role
For an undergraduate currently pursuing a bachelor’s degree in a quantitative or analytical field. Summer 2026 internship, with possible extension; exposure to Python, SQL, R, statistics, modeling, or data visualization is preferred.
About the employer
Risk Analytics Company is hiring for this role. Industry: Portfolio Management and Investment Advice. Sector: 52.
Additional details
- Industry sector
- 52
- Industry
- Portfolio Management and Investment Advice
- Occupation code
- 15-2051.00
You'll be redirected to the employer's application page.
Listing ID: 833c1405-4b5a-420c-9539-a9ca5db69d76