The growing demand includes Australia, with the country’s data science workforce forecast to increase to 339,000 in 2021-22 from 301,000 in 2016-17, representing an annual average growth rate of 2.4% – outpacing the 1.5% a year growth rate forecast for the Australian labour force as a whole over the same period.
The report — The future of work: Occupational and education trends in data science in Australia — from Deloitte Access Economics, says that as industries and governments worldwide race into the era of "big data", data scientists who have completed postgraduate IT study will have an average income of US$130,176 in 2021-22, up from US$111,634 in 2016-17.
The report finds that across workers who have completed a postgraduate IT qualification, a lifetime wage premium of 51% is directly attributable to their qualification compared to workers with no post-school qualifications.
“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 would 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.
“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.”
David Rumbens, partner, Deloitte Access Economics, said the projected wage premium stems from the greater skills and productivity of workers in the data science field who achieve postgraduate qualifications.
According to Rumbens, 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.
“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.”
Rumbens points out that 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 – while Harvard Business Review labelled it the “sexiest job of the 21st century”.
In addition to the technology sector, Rumbens says 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 among 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.
“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.”