MSc in Financial Engineering

The largest financial engineering program in the world is 100% online and tuition-free for everyone.

Degree: Master of Science
Length: 2 years

Our MSc is where programming and data science meet the future of finance.

Course graphic

This field is on the rise as financial innovation across the globe drives demand for analytics and data science training.

From evaluating statistics to econometric modeling, our educators teach advanced skills that can be used in the majority of industries. Graduates are prepared for sought-after positions in securities, banking, and financial management, and can also apply their skills at general manufacturing and service firms as quantitative analysts.

“Hiring skilled students who come from institutions like WorldQuant University is a business imperative.”
Susan Wolford,
Managing Director and Head of Technology & Businesses Services Group, BMO Capital Markets

What You’ll Learn

Designed by industry experts, WorldQuant University’s program integrates mathematical, statistical, and computer science tools with finance theory.

It is composed of fourteen courses and is designed to be completed in two years. Each course is sequentially taught and builds on the previous one. Taking one course at a time allows you to earn your degree without disrupting your life.

All courses are delivered online and focus on applied projects.

Course timeline

Course Descriptions

The MSc in Financial Engineering is comprised of fourteen courses. The course descriptions are provided below.

Course 1
Financial Markets I

The Financial Markets I course is intended as an introduction to Financial Markets.

Course 2

The Statistics course expounds on basic statistical concepts that are important in portfolio management.

Course 3
Programming in Python I

The Programming in Python I course covers the basics of Python Programming as it relates to Financial Computing.

Course 4
Algorithms I

The Algorithms I course covers the basic concepts of Algorithms. Students will learn about algorithms and their role in computing.

Course 5
Financial Markets II

The Financial Markets II course builds upon the foundation course Financial Markets I to demonstrate how the various instruments that were previously introduced are assembled to build portfolios.

Course 6
Programming in Python II

The Programming in Python II course covers advanced Python concepts related to Financial Computing.

Course 7

The Econometrics course covers econometrics as statistical methods as applied to finance, building on the concepts students were introduced to in Financial Markets I and II, Statistics and Python I courses.

Course 8
Alpha Design I

The Alpha Design I course will introduce the basic concepts related to statistical arbitrage within and across asset classes.

Course 9
Algorithms II

The Algorithms II course covers the core knowledge required to understand numerical algorithms for computational finance.

Course 10
Risk Management

The Risk Management course is an introductory risk management course that seeks to present a comprehensive overview of risk management to the uninitiated students.

Course 11
Alpha Design II

A follow-up to the Alpha Design I course, the Alpha Design II course provide the students with a deeper understanding of Alpha development and demonstrates the application of these concepts in the real world of trading.

Course 12
Machine Learning

The Machine Learning course covers the basic concepts of machine learning. Students will learn about principles and applications of statistical learning, machine learning and tools therein.

Course 13
Alpha Design III, with Machine Learning

A follow-up course to Alpha Design II, the Alpha Design III with Machine Learning course will elaborate in even more detail and increasing complexity a variety of alpha strategies.

Course 14
Capstone Course

The Capstone course is designed to put the students’ knowledge of financial engineering to the test.

Financial engineering whiteboard

How Can I Use My Degree?

Financial engineering whiteboard

Financial engineers pursue professional roles such as quantitative researchers, quantitative developers, quantitative traders, algorithmic traders, and portfolio managers for financial institutions.

Some focus on public policy, working for governments developing state and federal financial policies, or conducting research at think tanks.

There is a tremendous amount of fluidity between different financial-engineering careers, as well as transferable skills that allow professionals to easily move between these opportunities.

Learn more about careers

Where Are You Located?

Wherever you are.

We believe location shouldn’t be a barrier to education. We use a web platform so students can complete their entire degree online from anywhere in the world, at any hour of the day.

From Singapore to Nigeria, our student community collaborates with peers and educators with diverse backgrounds from around the world.

Wherever you are, join a community at the forefront of financial engineering.

Who Should Apply?

Our students are career-driven, computer-savvy quantitative thinkers. They have fully completed a bachelor’s degree or an equivalent 4-year degree and are interested in a future in financial engineering.

They come from a wide range of countries and have diverse backgrounds. They want to advance their career and seek life-changing education.

WorldQuant University weighs several factors in evaluating applicants. Academic records are prioritized, but we also consider professional work experience, professional references, civic leadership, and extracurricular activities.

What else is required?

Smiling photo 2

Detailed information about WorldQuant University, the program, requirements for admission, academic policies, and other considerations are available in the WorldQuant University Catalog.

You can view and download a copy here.

When Do Classes Start?

Courses run for six weeks with one-week breaks between course sessions, and longer breaks at the end of the year. Students can begin the first course in the program at any course session start date. There will be seven start dates every year.

2017 Start Dates

January 10
February 28
April 18
June 6
July 25
September 12
October 31

2018 Start Dates

January 9
February 27
April 17
June 5
July 24
September 11
October 30

2019 Start Dates

January 8
February 26
April 16
June 4
July 23
September 10
October 29

Get Started Today

I’m Ready

Frequently Asked Questions

Learn more about financial engineering, data science, the University, our degree programs, and admission.

Apply Online

Ready to get started? We will walk you through the application process and make sure you have everything you need.