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Master of Business Analytics

Arm yourself with computational statistical tools in the face of uncertainty.

Study at Monash Business School

By doing a Master of Business Analytics you’ll develop the skills to use data to better understand the world around you, opening doors to new exciting job prospects. In this degree, you will learn cutting-edge techniques, and rigorous foundations in statistical thinking, probabilistic modeling and computational techniques.

This degree will prepare you for a career as a statistician or data scientist, and your skill set will be relevant across all industries, giving you the freedom to join an area that inspires you. This is also an area of rapidly increasing demand across the corporate, government and non-profit sectors within Australia and internationally.

Our teaching staff have strong connections with industry and have worked with a number of major organisations. A small sample of these include: Facebook, Tennis Australia, Amazon,, AGL Energy, ABS - just to name a few.

Due to COVID-19, the University has transitioned all units online until further notice. We have some of the brightest educators who are continuing to provide all of the quality hallmarks of a Monash education in new and dynamic ways. Online, or on campus, Monash will help you prepare for a new future.

  • Location and duration

    Study on-campus full-time for 1.5 or 2 years or part-time for 3 or 4 years at Clayton campus – depending on prior qualifications. Day and evening classes are available.

  • Start in 2021

    Applications for our Semester 1 intake (February 2021) are now open.

  • Entry requirements

    An Australian bachelor's degree or an equivalent qualification, in a technical, mathematical or scientific discipline, with a Weighted Average Mark (WAM) of 65% or an equivalent GPA as determined by the School. You must have also passed an undergraduate statistics unit, or provide evidence of qualifications,

Why a Master of Business Analytics?

Our experts

Our academics are world experts in the field of data-driven decision making, with active and globally connected research programs. Many of the methods and software developed by our researchers are widely used in businesses and government departments today.

As part of a small and elite program, you’ll also work closely with our academics, resulting in more personalised assistance with your career development.

  • Rob Hyndman

    Head of the Department of Econometrics and Business Statistics and elected member of the International Statistical Institute, Rob's most recent work includes forecasting demand for electricity, estimating life expectancies, and forecasting product demand for a large telecommunications company.

  • Di Cook

    As a Fellow of the American Statistical Association and elected Ordinary Member of the R Foundation, Di’s worked with a number of leading corporations. Her research interests include data science, data visualisation, data mining, high-dimensional methods and statistical computing.

  • Anastasios Panagiotelis

    Anastasios conducts research on novel statistical methodology and its application to large datasets in energy, macroeconomics and online retail. He also led the project that launched, a website providing easy access to over 40,000 Australian macroeconomic variables.

  • Patricia Menendez

    Patricia’s research is on developing and applying statistical methodology and computational methods to answer real-life problems. She has worked with industry and government organisations developing multidisciplinary projects to answer research and policy decision-making questions in the fields of climate change, environmental and marine sciences besides criminology and social sciences.

  • Klaus Ackermann

    Klaus is a founding member of SoDa Labs, an empirical research laboratory associated that applies new tools from data science, machine learning, and beyond to answer social science questions using alternative and big data.

  • Emi Tanaka

    Emi is an applied statistician whose research interest is in developing high impact statistical methods and useful, easy-to-use tools for application in bioinformatics, biometrics and biology with a particular focus on agriculture.

  • Didier Nibbering

    Didier's research interests include high-dimensional inference, forecasting, and semi-parametric Bayesian inference. He holds a PhD in Economics and a BSc and MSc in Econometrics from the Erasmus University Rotterdam.

  • Catherine Forbes

    Catherine's research is in the areas of Bayesian time series analysis and financial econometrics. In addition to her peer-reviewed research publications and grant projects, she's also engaged in several contract research projects for a range of private and government organisations.

What our community says

We have developed an exciting and industry-relevant curriculum, taught by global leaders in the field. But don't just take our word for it. See what the international data community says.

Find out more

Interested in making your smartest investment yet? Find out more about the Master of Business Analytics.

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Ready to make your next career move? Find out more about entry requirements, course structure and how to apply.

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Graduate information session

Book a tailored online one-on-one session to find out how a graduate degree with Monash Business School can open up a world of opportunities for you.

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