Why experts are calling data science the sexiest job in the world

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Big data scientists are entering the world of healthcare, and the impact is set to be revolutionary.

By Ken Eastwood and Belinda Smith

It’s not often that an occupation is crowned “sexiest job of the century” only a few years after it pops up. But data scientists have bucked the trend and are reigning supreme in the job market – and they’re reaping some impressive benefits as a result.

Proficient at navigating vast oceans of information to fish out hidden trends and patterns, data scientists are at the forefront of computer science and artificial intelligence (AI). They develop software and algorithms to target the information they’re seeking and then, from that mind-numbingly massive coalface of big data, they extract invaluable insights for their clients.

To give you an idea of why data scientists have become so invaluable, consider that the global volume of online information is estimated to be growing at more than 50% each year, and the number of organisations storing 1 million gigabytes (a petabyte) has doubled since 2014. 

Now, less than a decade since LinkedIn and Facebook analysts popularised the term “data scientist”, it’s become one of the most coveted roles for ambitious, tech-savvy individuals, with some of the world’s most successful companies like Google and Walmart scrambling to snap them up.

It’s a lucrative gig, too: the median base salary is A$130,000, according to a survey by the Institute of Analytics Professionals of Australia.

And that’s why back in 2012, the esteemed Harvard Business Review bestowed the title of “Sexiest job of the 21st century” on data scientists.

Think of him or her as a hybrid of data hacker, analyst, communicator, and trusted adviser,” write The Review’s Thomas H. Davenport and D.J. Patil. “The combination is extremely powerful – and rare.”

Leading a healthcare revolution

 In the healthcare sector, data scientists are now coming into their own - particularly with the recent opening of UNSW’s world-leading Centre for Big Data Research in Health (CBDRH).

Using large-scale electronic data that spans the biomedical, clinical, health services and public health domains, the Centre brings together more than 60 research staff and students to tackle critical health issues facing the Australian and global communities.

I love it because it’s so stimulating,” says Professor Sallie-Anne Pearson, head of the Centre’s Medicines Policy Research Unit, which uses big data to determine how medicines are being used locally and internationally.

It’s science, but there’s a lot of art in this.”

Nutting out how we use medication is just one of the many facets of the Centre’s research expertise. Revolutionising how we treat cancer is another big focus.

It’s predicted that this year alone, more than 134,000 new cancer cases will be diagnosed in Australia. To better understand factors that influence patient outcome, the Centre’s Cancer Epidemiology Research Unit mines public health data that’s been collected nationwide to assess the care patients receive compared to what is recommended.

The greatest insights are likely to come from the intersection of data on human genetics and human behaviours known to increase our risk of cancer, such as smoking,” says the unit’s head, Associate Professor Claire Vajdic.

With big data regarded as the best tool we have to solve the lingering mysteries of human biology, it’s also being used to shine a light on the enigma of human fertility. At the CBDRH, Associate Professor Georgina Chambers’ National Perinatal Epidemiology and Statistics Unit have for the first time come up with accurate predictions of success rates for several cycles of IVF - crucial insight for couples who can afford multiple attempts at assisted reproductive technology.

Meanwhile, UNSW’s Health Services and Outcomes Unit, headed by the CBDRH’s foundation director, Professor Louisa Jorm, aims to give Indigenous children the best possible start in life. The Unit’s Seeding Success program incorporates data on hospital admissions and child development for example, to throw light on this important but under-researched area.

Data scientists in the health sector can’t rely on their technical skill alone, says Peter Cronin, co-founder and managing director of Prospection, a Sydney-based health insights company. They also need people skills, communication skills, and an inquiring mind.

“Being a good data scientist in this sector means first being able to understand what is the question that someone wants to ask. Then you need to understand the data you’re working with, including the limitations of that data,” Cronin explains.

“Thirdly, you have to be able to develop algorithms. And the fourth component is knowing how to communicate or visualise the answer to be able to present it to the client.”

He adds that having a health background helps in understanding the wider context, but if a data scientist doesn’t have that knowledge, it’s vital that they work alongside those who do.

Date Published
Thursday, 5 October 2017

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