2025 MFE Programs Rankings Methodology

Master programs in Financial Engineering, Mathematical Finance, Quantitative Finance were surveyed on admission, placement, and career services information. All invited programs provided the data needed to calculate the rankings based on a weighted average of the categories described below.

Unless otherwise stated, all admission data refers to the incoming cohorts starting in 2024 and the graduating class of 2024.

Peer Assessment Score (20%)

Each program was asked to rate all programs in this year ranking from 1 (marginal) to 5 (exceptional).

Placement Success (55%)

  • Employment Rate at Graduation (10%)
  • This is the employment rate for the latest FT graduate cohort at their graduation.
  • Employment Rate Three Months after Graduation (15%)
  • This is the employment rate for the latest FT graduate cohort 3-month after their graduation.
  • Average Starting Salary and Sign-on Bonus (US) (20%)
  • The average starting salary and sign-on bonus of the most recent FT graduate cohort who received full-time employment in the US.
  • Employer Survey Score (10%)
  • Employers were surveyed to identify which of the programs in this year's ranking whose graduates they have interviewed or hired from within the last two years.

Student selectivity (25%)

  • Undergraduate GPA (17.5%)
  • This is the average undergraduate grade-point average of those most recent incoming cohort of the program.
  • Acceptance Rate (7.5%)
  • This is the percent of FT applicants to the program who were accepted.

Overall score

A score for each program is accumulated from the points in each category multiplied by the category's assigned weighted average. The final scores were rounded to the nearest integer. A tie is determined if any two or more programs have the same final score and tied programs are listed alphabetically.

Programs that did not provide placement data or salary information meeting a minimum threshold were not ranked.

Disclaimer: We rely on the programs featured in our rankings to provide accurate data. QuantNet assumes no responsibility for inaccuracies, as the data submitted is not audited by any third-party agency.

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