Why the demand for data scientists is increasing

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Why the demand for data scientists is increasing
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One of the by-products of the digital transformation is the growing need for data scientists.

That’s not surprising when you consider changes in consumer buying behaviour. What consumers once did in-store is now more-likely done online using a smartphone. And that opens up new opportunities to map buyer behaviour and identify consumer purchasing patterns.

Retailers are seizing these opportunities. Retailer Woolworths has previously advertised job openings for data scientists, iTnews reported. The roles included head of data science engineering and big data engineer. One job advertisement explained that the company’s data science team would help drive greater customer loyalty.

Salaries have consistently increased for marketing professionals who specialise in data science, according to recruitment company Hays. It reports a shortage of data insight managers and analysts and people who can pull data together to “articulate an engaging narrative”. This provides further job opportunities for those with the skillset to fill these specialised roles.

Data scientists can work across the fields of health, finance, manufacturing, IT, user design and government. By analysing huge data sets, they can find ways to improve processes and outcomes and minimise risks.

Big issues

The variety of data science roles makes it an exhilarating career path. Jobs include everything from business analyst to machine learning programmer and data-mining engineer. Data scientists might identify medical and health issues, help government agencies identify effective policy areas, or enable businesses to perform better.

For example, ANZ Banking Group has a “next generation big data ecosystem” and is using deep learning to help unlock the power of its data.

At Woodside Energy, data scientists have created an artificial intelligence assistant which allows the use of natural language when asking queries. One goal of the assistant is to help employees work more productively by finding information faster.

And last year, Rio Tinto CEO Jean-Sébastien Jacques spoke about the importance of data scientists to the company, highlighting the shortfall of data scientists they face. “I’ll make a forecast that ten years down the road I will still need 100 engineers, but the ratio will be totally different: one-third mining engineers as we know them, and two-thirds would be telecom, data scientists and so on,” he said.

Technology skills

Data science might be attractive to someone wanting to work with machine learning. They could create machine learning algorithms that analyse vast archives and virtual warehouses to find patterns.

They could use data visualisation to make results palatable to stakeholders and enable them to easily understand and act on new information.

Top data scientists often have an aptitude for mathematics and statistics, as well as basic coding skills that enable them to create basic scripts such as Python scripts though these skills aren’t mandatory.

Studying data science typically involves multi-disciplinary coursework to tie all of the above skill-sets together. Median salaries for qualified workers are well above $100,000, according to the Institute of Analytics Professionals of Australia.

The good news for people interested in data science, is that it’s possible to gain qualifications online from top-tier universities. For example, UNSW Online offers a Master of Data Science course, which includes a broad range of foundational skills covering everything from data and ethics to regression analytics.

This broad skill set will not only help graduates land data science roles now, but it may even help them step into roles in the future that don’t exist today.

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