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Universities / London School of Economics and Political Science

MSc Stochastic Finance and Machine Learning (formerly Quantitative Methods for Risk Management) (QMRM)

A demanding programme combining stochastic modelling, statistics, machine learning and AI with practical workshops on real data. Succeeds the MSc Quantitative Methods for Risk Management.

What you’ll study

Core

  • MA400 September Introductory Course
  • ST409 Stochastic Processes
  • ST429 Statistical Methods for Risk Management
  • ST463 Stochastic Simulation, Training, and Calibration

Electives

  • Five half-unit options in statistics, machine learning, AI, specialised finance (market microstructure, derivatives, interest rates, risk analysis) or probability and mathematics

Source: lse.ac.uk ↗

Before you apply

Background
2:1 or equivalent in mathematics, statistics, actuarial science, mathematical economics/finance or another highly quantitative subject
Maths
advanced mathematics and statistics coursework
Tests
Not mentioned
English
Standard LSE level
Other
Personal statement (500 words), two references, CV, course descriptions and reading lists

Source: lse.ac.uk ↗

After graduation

Typical first roles
Quantitative roles at banks, asset managers and hedge funds, Insurance, Auditing, Consulting, Data science
Employers
Barclays, HSBC, Santander UK, Credit Agricole CIB, CITIC Securities, Man Group, Goldman Sachs

Source: lse.ac.uk ↗

Want to see what employers ask for? Browse open quant roles.

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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.

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