MS in Financial Engineering (MSFE)
A financial engineering master combining optimisation, stochastic modelling, simulation and statistical analysis with finance. Concentrations span asset management, computational finance, derivatives, fintech and machine learning, supported by a quantitative bootcamp and practitioner seminar.
What you’ll study
Core
- MSFE Quantitative and Computational Bootcamp (0 credit)
- Optimization Models and Methods (FE)
- Stochastic Models (FE)
- Foundations of Financial Engineering
- Professional Development and Leadership (0 credit)
- Financial Engineering Seminar Series (0 credit)
- Monte Carlo Simulation
- Financial Engineering: Continuous Time Models
- Statistical Analysis and Time Series
Electives
- Applications Programming for Financial Engineers
- Machine Learning for Financial Engineering and Operations Research
- Quantitative Risk Management
- Term Structures and Credit Models
- Credit Risk Modeling and Derivatives
- Programming for Financial Engineering
- Deep Learning for Operations Research and Financial Engineering
- Asset Allocation
- Computational Methods in Derivatives Pricing
- Algorithmic Trading: Theory and Practice
Source: ieor.columbia.edu ↗
Before you apply
- Background
- Quantitative background in engineering, mathematics, computer science, statistics, economics, finance or a similar field; three-year bachelor applicants may apply, with four years recommended.
- Maths
- Calculus, including multivariable calculus; Linear algebra; Probability and statistics; Differential equations advantageous
- Programming
- Coding proficiency expected; Python mastery described as essential for MSFE preparation.
- English
- English test may be required, with degree-country exemptions. FAQ states no minimum score to apply; it flags proficiency improvement at TOEFL iBT 4.5 or lower on the new scale (tests after 21 January 2026), earlier TOEFL 99 or lower, IELTS 7.5 or lower, PTE 68 or lower, or Duolingo 130 or lower. These are advisory flags, not admission cutoffs.
- Other
- Finance knowledge in derivatives, risk management, portfolio theory and markets expected. Three recommendations (normally at least two academic), video interview; professional experience recommended. FAQ prefers GPA 3.0/4.0 or higher. GRE policy for a specific future intake is not definitively stated on the FAQ.
Source: ieor.columbia.edu ↗
After graduation
- Employment
- 93% placement reported for the 2024–2025 MSFE cohort: 115 started in Fall 2024, 102 received employment offers and 5 continued education. The report does not state a months-after-graduation deadline or explicit rate denominator.
- Typical first roles
- Quantitative Analyst, Quantitative Researcher, Quantitative Trader, Trading Desk Analyst, Risk Analyst, Portfolio Analyst, Exotic Trader
- Employers
- Bank of America, Barclays, BlackRock, Citi, Goldman Sachs, JPMorgan, Morgan Stanley, Millennium Management, Point72, Squarepoint Capital, The Voleon Group
Source: ieor.columbia.edu ↗
QuantNet’s 2026 ranking reports 2025 full-time graduating cohort: 79% employed at graduation; 87% employed three months after graduation employment and a US$138,000 reported compensation figure for the 2025 full-time graduating cohort. The table labels this “Base salary”; the methodology defines average starting salary and sign-on bonus. Components are not reconciled by the source; this is not a median. starting salary. See the ranking ↗
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.
- Columbia University – Masters in Financial Engineering: student reviews (QuantNet)
- MSFE Columbia (Reddit)
- Thoughts about Columbia MFE (Reddit)
- QuantNet programme profile and reviews: Columbia University — MS in Financial Engineering (QuantNet)
STEM-certified. Employer examples are companies making at least one full-time offer, not an employer ranking. The report publishes US-based average salary US$126,946 and average bonus US$30,970; no median is published, and base-pay definition is not explicit. GRE entry remains null because FAQ only recommends preparation for future cycles based on historical requirements.
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.