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Data scientists with around 5 years\' experience are earning over 75 lakh per annum as compared to 8-15 lakh for CAs and 5-8 lakh for engineers with the same experience level.
MUMBAI: In 2012, Harvard Business Review named data scientist the "sexiest job of the 21st century". More recently, Glassdoor named it the "best job of the year" for 2016. In India, too, companies are scrambling to hire data scientists, sending salaries soaring.
According to TeamLease, a staffing solutions company, data scientists with around 5 years' experience are earning over 75 lakh per annum as compared to 8-15 lakh for CAs and 5-8 lakh for engineers with the same experience level.
So who exactly are data scientists? It's a loose term but these are the guys who know how to look at the data a company generates, and derive the all-important insights it needs to garner more business and enhance customer experience in this age of social media.
With companies across industries striving to bring their research and analysis (R&A) departments up to speed, the demand for qualified data scientists is rising.
"India will face a demand-supply gap of 2,00,000 analytics professionals over the next three years. Even in the US, only 40 out of 100 positions for analytics professionals can be filled," said Rituparna Chakraborty , co-founder & senior VP of TeamLease Services.
In the US, data scientists get upwards of $2,00,000 per annum.
Data analytics professionals are primarily mathematicians, statisticians, database/data warehouse engineers, data miners and IT professionals with data warehousing skills.
A data scientist is a hybrid of many of the above listed skills and, therefore, a rare breed. To meet their talent requirements, some companies have come up with unique programmes.
WNS, which is in the business process management industry, has created a fully funded post-graduate MBA programme in business analytics customised around its needs. All students completing the programme would be absorbed by WNS.
Keshav Murugesh, Group CEO of WNS, said: Business models are changing across the world. A lot more data is available and companies want to provide focused, prescriptive solutions. If analytics is going to play such a big part, we need to make sure we have the right kind of talent and skills inside the company to feed those programmes.''
WNS currently draws 13% of its revenue from research and analysis, and believes there is further growth potential. In a competitive world, companies like WNS want to leverage data using interactive models, algorithms, automation and then create predictive-based analytics to serve clients better.
Two years ago you wouldn't be talking about data scientists, social architects or anthropologists working in a company," pointed out Prithvi Shergill, CHRO at HCL Technologies. But now a lot of people are very keen to align their long term careers around analytics.
However, curriculums have not evolved fast enough and this is not restricted to India alone. US-based thought leader and HR consultant, Jason Averbook, said: In addition to maths and statistics, there is also a requirement for people with marketing communications. It's this combination of maths and marketing communications that'll create storytellers so that data can be used and turned into a story. The whole of people are very keen to align their long term careers around analytics. Curriculums are being changed but the best people are doing it on their own.''
Averbook, who was in India recently as the keynote speaker at SHRM Tech HR, told TOI that companies should hire freshers. "Twenty year olds are much more equipped at data than forty year olds. The sooner companies can get their hands on those who really understand data and then teach them their business, the better. It's hard to reskill.''
Shergill, however, believes such talent also needs to be built from within through re-skilling. Although organizations are grooming existing analysts and senior managers with analytical aptitudes for data scientist roles and building the talent pool in-house, advanced analytics skills are not easily learned. Some managers go for formal training and certification in advanced analytics and companies are encouraging the same.
Read More: http://ow.ly/TJXk3002XmL
source: techgig.com
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