The Rise of the Data Scientist

There is no better time to be a Data Scientist in Australia. According to the Institute of Analytics Professionals in Australia (IAPA) data scientists with business acumen are in such high demand, they are earning almost three times Australia’s average salary.

In this digital world, 2.5 quintillion bytes of data are created every day and this continuous flow of information can mean the ability to forecast market activity, understand customer behavior, and build strategies accordingly. But, in order to understand and unleash this predictive power, businesses need professionals with data science skills. By the end of this year, the McKinsey Global Institute predicts this specific data science talent shortage could top 190,000 hires in the USA alone.

But what exactly do data scientists do and why is it such a great job?

Think of the data scientist in a business as the company detective, delving into all the given intelligence or data a company can glean, across all parts of the business, and then makes sense of them for better business outcomes. It’s an important role and a good data scientist can transform a business. So, as more and more companies are coming to realise their own data is one of the most powerful assets they have, the need to collate, understand and express this data is growing every day.

The classic demand and supply situation would tell you that good data scientists are paid a pretty penny and the job opportunities are plentiful – in some industries more than others.

Larger businesses with an interest in the Internet of Things, eCommerce or Finance are especially looking for experienced Data Scientists. And the wealth of jobs for data scientists is growing in wildly exciting and fast-moving industries, such as tech-innovation, startups and tech-disruptors of many industries.

What employers will be wanting are honed programming and tech skills in all sort of data modelling, predictive modelling and dashboarding, with an ability in the languages R, Hyphen, Python and SQL. Depending on the data scientist, you can use Tableau or more recent big data tools like Hadoop.

In Emerging Tech generally, be it startups or tech companies developing IoT innovation, most employers are looking for managers with a combination of product design, development and architecture. If you have a background where you can grasp the hardware product first and then the software, ie having worked on both sides of the scale to integrate the two – you will be extremely hireable.

The IoT industry is where data scientists and a range of other emerging tech professionals can flourish and excel. A Head of IoT, usually a data scientist, can earn $250K to $450K depending on the size of the company.

Other connected roles that are on the rise are Data Engineers and a new addition to the C-Suite – the Chief Data Officer (CDO).  Essentially, Data Engineers extract the information or data for the Data Scientist. The CDO, along with the Chief Analytics Officer (CAO), make up a growing number of executive boardrooms that are creating a culture of analytics. They manage all issues to do with data security, insurance and governance.

For data science professionals and those involved in the world of acquiring and interpreting information, there are very interesting and lucrative times ahead. The future will belong to data scientists who can continuously improve productivity and give the organisations they work for, a competitive edge.

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