Solving the World’s Problems with Data Science

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Solving the World’s Problems with Data Science

ST Engineering’s Data Analytics Strategic Technology Centre (DA STC) was set up to build a deep digital technology core in Data Analytics capabilities and its associated enablers to bring value to the Group’s businesses by (1) translating differentiated technologies to products, (2) identifying technology potential, (3) transforming work processes, and (4) sharing analytical insights. Together with the business sectors’ digital teams, the DA STC forms ST Engineering’s deep capability core with a total of 80 Data Scientists, Data Engineers and Data Analysts who develop machine learning algorithms, mine data, and generate analytical insights.

 

“Data Science is a philosophical discipline. To be a good data scientist, you usually have to think on that level,” said Dr Alex Chung, who is the Principal Data Scientist from the ST Engineering DA STC. He holds a PhD in data science in the area of robotics and automation and has been in the data science field for close to 10 years. Before ST Engineering, he held positions at the National University of Singapore, the Port of Singapore Authority and DSO National Laboratories.

“Thinking from that level allows one to begin solving a problem elegantly. And to make inroads into the solving the problem, one has to continually refine his thinking,” said Alex. “I don’t just think when I’m at my computer. I think when I’m walking. I think when I am eating. I keep thinking. It doesn’t stop – you try to find a way, the best means to solve the problem. You’ve got to keep thinking.” Alex adds that elegant and easy-to-use solutions emerge only “after a lot of mental battles with the problem”. This is especially since data scientists need to translate differentiated technologies to products.

With all these considerations in view, there is certainly more to coming up with data science solutions than knowing which methods to apply. A good data scientist will need to understand problems in a technical and mathematical way, and appreciate why a problem should be solved in a certain way over others. They also need to find simplicity in complex problems so that they can eventually create new possibilities and transform work processes for their stakeholders and customers. This is why Alex recommends that aspiring data scientists explore taking a PhD to help them think and work with data more conceptually.

The complexities inherent in data-driven solutions also mean that data scientists benefit from coming together in multidisciplinary teams to think and work together on innovative data-driven solutions. Alex explains that contrary to common belief, data scientists are specialists in their own rights, rather than generalists. Similar to how you would not ask a paediatrician to treat a heart problem, data scientists while trained in data science methods, would create greater value by bringing their points of view as specialists of certain subject areas to the table. The healthy debate between them will also foster new ways of thinking.

Meanwhile, working in the ST Engineering DA STC affords Alex the opportunity to work on cross-sector problems spanning the aerospace, electronics, land systems and marine sectors. Alex added that compared to academia where the outcome is usually a prototype, data scientists in industry “address urgent needs” and create solutions targeting a customer’s immediate problem.

Perhaps this is also why for “data to be the new oil”, the differentiating factor needs to be the creative mind. Solving real-world problems involves data scientists looking beyond mere historical and predictive analysis of data. To create value in a digitalised world, data scientists will need to conceptualise new paradigms and use-cases with data, which will in turn help customers create new value propositions and possibilities for their stakeholders. This is what the data scientists at ST Engineering’s DA STC are hard at work doing daily, as they think of ways to solve the world’s problems through data science.

With people as its core strength, ST Engineering is building a world-class workforce that is future-ready, and equipped with breadth and depth in technology and engineering capabilities. The Strategic Technology Centres are just one of the Group’s efforts amongst several others.

Data Scientist at work
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