The State of Data Science in APAC

HYPERLAB co-founder Chris Greenough gives us the lowdown on being #DataDriven in APAC.

As early as 2012, CXO’s of progressive companies were often quoted as saying “every company is a technology company”, followed in 2014 by the Big Data hype the mantra shifted to “every company is a data company”. Now in 2017, the war-cry has now shifted to “every company needs an AI strategy”. Whatever your position on these statements, it is clear that companies are increasingly focused on #DataDriven strategies as they seek growth during these transformative years.

The Challenges

One of the largest challenges to becoming #DataDriven is gaining adequate literacy throughout a company and hiring the right skillsets to help create and deploy a company strategy. Finding the right people at the right price is no easy task.

For example, if you are seriously venturing into artificial intelligence, you are competing with global Tech Giants in attracting the best talent. Independent Canadian AI lab, Element AI, believes that “fewer than 10,000 people have the skills necessary to tackle serious AI research” in the world.

10,000 may not sound like a lot. But after reviewing the amount of Linkedin profiles who claim to have skills related to AI, that represents about about 0.095% of global talent who meet the standards which Element AI holds to “tackle serious artificial intelligence research”.

So how can companies in APAC even consider building a data-led, machine learning business or practise when only 1 in every 1,000 candidates are qualified?

Unfortunately, supply isn’t the only challenge.  Linkedin recently released a report on the The Digital Workforce of the Future where they found the  top 3 in-demand skills to be Artificial Intelligence, Big Data, and Cloud computing – dubbed “ABC talent”.

Digging a bit deeper into Linkedin’s data, and searching for skills related to data science and machine learning, APAC only has about 16% of the global talent pool for these skills, of which a large proportion are being hired by large technology and consultancy companies. Some of the top companies include Infosys, Tata Consultancy, Amazon, and Accenture.

But in such a fast-moving field with high demand, it’s hard to find someone in data science or machine learning who has been in their current role for more than a year or two, making these roles incredibly valuable but also incredibly fragile.

Are things looking up?

Fortunately, the future for data science talent in the region looks bright. Regionally, more than 65,000 students will graduate between 2017 and 2024 who will have the skills needed to build a #DataDriven business (and that’s just what’s reported on Linkedin).

Where Linkedin’s report cited India, Australia, and China as the largest source of ABC talent, it looks like Malaysia and Singapore should also be highlighted for its contribution. As co-founder of a Conversational AI company in Malaysia (HYPERLAB), this was a very exciting finding. Malaysia for example, added another 4,000 graduates this year who have the skills to become Machine Learning Engineers.

Some of the top universities in APAC where future graduates will come from include Nanyang, National University of Singapore, University of New South Wales, Birla Institute of Tech, and the University of Mumbai.

Institutional Universities are not the only ones who are training the future talent pool, online education hubs like Udacity and Coursera are also contributing to it in a large way. Almost 10% of all recently trained data science talent in 2017 was educated by an online learning platform – and there’s no sign of it slowing down.

“Almost 10% of all recently trained AI talent in 2017 was educated by an online learning platform.”


Admittedly this is not an exhaustive study and it depends largely on the penetration of Linkedin in certain markets. But, it does generate some insight on what companies in APAC, especially smaller companies, need to do in order to attract, retain and grow their talent pipeline if they are to build a #DataDriven business.

Chris’ Top 3 Tips

  1. Build a pipeline: Start your talent pipeline now, there are a lot of great graduates coming out of schools in the region who will be part of the future workforce who will be able to tackle serious AI challenges. If you’re small, don’t discount your ability to attract this talent.
  2. Plan to retain, plan for turnover: These positions can have high turnover, so you need a strategy to retain and protect this talent from large Tech Giants and consultancy firms.
  3. Online Learning: Don’t discount those with online learning credentials, the most talent you’ll have access to are new to this field as well. Upskilling existing employees with deep industry experience should also be a strategy you look at.


Speaking of learning, if you want to start being #DataDriven, keep a look out our workshops in Australia, Singapore and now Hong Kong! We run these every quarter and cover the whole suite of the data-scape: from basics to expert workshops.


Guest writer Chris Greenough is the CMO and co-founder at HYPERLAB, with over 7 years of experience helping businesses across APAC transform their businesses for the digital age. He’s the co-founder of HYPERLAB – a conversational AI company that builds cognitive customer experiences for leading enterprises in Asia.

Check out HYPERLAB‘s website and Linkedin to find out more.



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