Salaries Set To Soar For Aussie Workers With Big Data Skills

As industries and governments worldwide race into the era of ‘big data’, demand for data science professionals will jump, pushing up salaries and boosting employment opportunities, particularly for professionals with postgraduate qualifications.

A new report prepared by Deloitte Access Economics, The future of work: Occupational and education trends in data science in Australia, predicts that data scientists who have completed postgraduate study in Information Technology will have an average income of $130,176 in 2021-22, up from $111,634 in 2016-17.

Employment forecasts for the data science workforce by component occupations

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The report finds that across workers who have completed a postgraduate qualification in Information Technology, a lifetime wage premium of 51 per cent is directly attributable to their qualification compared to workers with no post-school qualifications.

David Rumbens, partner, Deloitte Access Economics said this wage premium stems from the greater skills and productivity of workers in the data science field who achieve postgraduate qualifications. The data science field itself is rapidly gaining in importance.

“The rate at which information and data is being generated is faster than ever before … The proliferation of new and existing technology platforms – such as sensory networks and augmented or virtual reality – has contributed to this growth in big data. This trend has been driven by advances in computing power, exponential growth in internet data usage and the shift to cloud computing,” he said.

“The benefits that organisations can gain from analysing this big data has led to growing demand for data science skills, with increasing applications of techniques such as data mining and machine learning across many industries throughout the economy,” Mr Rumbens said.

LinkedIn named ‘statistical analysis and data mining’ as leading the list of Top Skills of 2016 in Australia and found data science was the second-most sought-after job skill in 2016 in the US and globally. Harvard Business Review labelled it the “sexiest job of the 21st Century”.

In addition to the technology sector, a broad range of other industries such as finance, health and medicine, defence and agriculture are beginning to rely on analytics in order to enhance their core activities and product offerings.

“However, roles which require this combination of skills are amongst the hardest jobs to fill. With data science capabilities becoming increasingly valued across many industries throughout the economy, further study in this area can provide new career opportunities and accelerated progression to senior roles,” said Rumbens.

“Further study in the data science area can also build core technical competencies for individuals currently employed in other areas enabling them to pivot towards data-related roles and enable the development of a greater understanding of the strategic and business applications of data analytics.”

The Australian data science workforce is forecast to increase to 339,000 persons in 2021-22 from 301,000 persons in 2016-17, representing an annual average growth rate of 2.4 per cent, the report reveals. This outpaces the 1.5 per cent a year growth rate forecast for the Australian labour force as a whole over the same period.

James Cook University (JCU) lecturer in data science, Dr Neil Fraser, said there are a wide variety of job opportunities available to individuals with data science skills.

“These include roles in the technology sector, with large technology companies such as Google, Facebook, Netflix and Amazon utilising data analytics and machine learning techniques within their core product offerings. Organisations in other industries – such as finance, retail and agriculture – are also increasingly making use of data science capabilities in order to improve productivity and sales,” Dr Fraser said.

“Computer programming skills will remain fundamental to the data science area, to ensure individuals build familiarity with computer languages such as R, Python, SQL, SAS, MATLAB and Excel. At the same time, there is a need to develop an understanding of the whole lifecycle of data, including the acquisition, management and pre-processing of data, as well as mathematical and statistical analysis, visualisation, reporting and decision making,” Dr Fraser said.

“Understanding this lifecycle is crucial for working with data in any industry or government organisation, as using raw data to produce meaningful business insights is the core task required of data scientists regardless of the particular sector that they work in,” he said.

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Big Data Deloitte Access Economics James Cook University