Anirban Dey, vice-president of in-memory platform technologies at SAP Labs, works with a 100-member team. Most of them are engineers involved in software development or quality management, but roughly a fifth are researchers who look a few years into the future.
Researchers are part of many large R&D centres, but some of Dey’s team members are specialists in Natural Language Processing (NLP), who would have found it difficult to fit into IT companies other than a Google or a Yahoo.
“NLP experts are now becoming more mainstream given the current focus on social analytics in customer engagement,” says Dey. As companies increasingly start analysing data, and the nature and size of data make insights more and more difficult, a new set of specialists is suddenly in great demand.
SAP Labs doesn’t have a name for them, but they are known in some companies – like IBM, EMC and HP – as data scientists, a phrase coined more than a year ago for someone with special skills to analyse data. Data scientists command a premium over software engineers, but companies don’t typically hire them in large numbers.
“Data scientists would get at least a 30% to 40% premium in compensation benefits when compared with software engineers,” says Arnab Chakraborty, head of global marketing for HP Global Analytics. The company, which has a strong presence in India, hires engineers with some experience and domain expertise.
Many of its employees have advanced degrees, with expertise in subjects like statistics, computer science, economics and applied mathematics. But data scientists also include business domain experts with strong data analytical skills, and managers who know how to work with large, fastflowing data.
Data analytics is not a new phenomenon, but its power and penetration among companies have increased tremendously in the past few years, causing the surge in demand for data scientists. A report by the McKinsey Global Institute last year predicted a surge in big data usage and a major shortage of those who can handle the relevant technologies.
By 2018, the US alone would have a shortage of 1,40,000 to 1,90,000 people with deep analytical skills and 1.5 million managers and analysts who know how to take good decisions using data. Many business schools and universities around the country are beginning to design courses to meet the shortage of data scientists.