MS in Quantitative Finance and Risk Analytics (QFRA)
A STEM-designated master focused on financial modelling, quantitative risk and financial technology. The programme describes practical work with financial data and tools including Python, R and MATLAB.
What you’ll study
The programme doesn’t publish a unit list. Check the programme website for the current structure.
Before you apply
- Background
- Finance, economics, maths, engineering or computing background preferred; other fields welcomed
- Programming
- Coding experience helpful, not required
- Tests
- GMAT/GRE optional for most Lally master’s programmes; verify programme-specific application rules
- English
- International applicants submit TOEFL or IELTS
- Other
- General Lally minimum GPA 3.0;3.3 preferred; recommendations, statement and CV
Source: lally.rpi.edu ↗
After graduation
- Typical first roles
- Quantitative Risk Analyst, Credit Risk Specialist, Finance Portfolio Manager
- Employers
- Bank of America, Merrill Lynch, Goldman Sachs, JPMorgan Chase, IBM, Citibank, Boeing, GEICO
Source: lally.rpi.edu ↗
Want to see what employers ask for? Browse open quant roles.
What students and graduates say
Threads from QuantNet and other forums where applicants, students and graduates discuss this programme. They’re personal views and may be out of date.
- Rensselaer Polytechnic Institute - MS in Quantitative Finance and Risk Analytics - Student reviews (QuantNet)
The programme is STEM-designated. General quant-industry salary references on its website are not a dated alumni outcome statistic.
Checked 6 November 2026 against the sources linked on this page. Fees, units and requirements change each year, so confirm them on the programme’s website before applying.