Big data, big deal: What a career in data science really takes

When we talk about big data, we often picture the giant tech companies: Facebook, Amazon, Google.

But skills in statistics, business analytics and data science are increasingly sought-after across a range of organisations and industries you might not have thought of – such as retail, healthcare, the environmental sector and not-for-profits.

Data isn’t just driving business decisions; it is helping shape policy and being applied to the big-picture challenges such as climate change, energy policy, infrastructure and agriculture.

The growth in artificial intelligence, data science and big data analytics will create 2.7 million new jobs world-wide until 2020, according to a forecast by PricewaterhouseCooper.

In its 2019 Jobs Rated report, the US jobs site CareerCast reported a 30 per cent increase in demand for statisticians or data scientists. Because of the high demand, salaries are booming.

What do you need to move into this sector, or boost your employment appeal?

This clearly isn’t an area for a basic beginner. But if you already have an undergraduate background in maths, engineering or computer science or equivalent real-world experience, then this is the ideal foundation for a career in data science and business analytics.

If you’re already working in this field, concepts such as statistical thinking, probabilistic modelling, computational techniques won’t sound foreign to you and will help you translate the raw data into statistical models and data visualisations that tell clear stories and provide advanced business insights.

Professor Rob J. Hyndman, an internationally known statistician at Monash Business School, uses the power of large data sets to address forecast demand for electricity and estimate expenditure on Australia’s Pharmaceutical Benefits Scheme, among other research topics.

He is set to teach into the new Monash Business School Master of Business Analytics program, starting in 2020. It was developed to address the burgeoning industry demand for these specialist skills.

“Everyone needs forecasts to help them plan for an uncertain future. And no matter what business you’re in or what industry you’re working in, having some idea about what possible things could happen in the future is going to be really helpful for planning for that,” he says.

Professor Dianne Cook, one of the world’s top statisticians and the third woman globally to be elected to the R Foundation, a body that supports the open source programming language ‘R’, is course director and one of the lead course developers

“The Master of Business Analytics is developed to train the next generation of data scientists. There are a lot of new and exciting job prospects in this field,” Professor Cook says.

One of the basics of the course is an introduction to data analysis and machine learning, the way that systems automatically ‘learn’ that underpins artificial intelligence. The course then moves on to ‘mastery knowledge’ that includes advanced statistical modelling.

It also has an applied component, as it is vital to transform theoretical knowledge into practice in the real world.

Monash Business School has a long track record of excellence in data science and business analytics and many staff conduct research and consulting with major organisations around the world such as Amazon, Facebook, Tennis Australia and AGL Energy.

For those already doing this sort of work, staying up-to-date is essential with a rapid growth in available statistical tools, Professor Hyndman says.

“The models are getting more and more complicated and the data sets are getting more and more rich, with lots of different variables and a lot more data being collected,” he says.

Ready to transform the world of business through data?

Find out more about Monash Business School’s Master of Business Analytics.

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