Why “Data Scientist” Is The Best Job in 2017?

data scientist is the best job

Data scientist the “sexiest job of the 21st century” – Harvard Business Review. More recently, Glassdoor named it “data scientist is the best job of the year” by 2016. In India also companies are eager to hire data scientists and offering high salary.

According to Team Lease, a staffing solutions company, Data scientists with about 5 years of experience are gaining more than 75 lakh per year compared to 8-15 lakh for CA and 5-8 lakh for engineers with the same level of experience.

So who exactly are the data scientists?

Individuals who know how to look at the data that a company generates, and derive the all-important insights it needs to accumulate more business and enhance the customer experience in this age of social media.

Click here to know more about “8 easy steps to become a data scientist

Rituparna Chakraborty, co-founder & senior VP of TeamLease Services said, “India will face a demand-supply gap of 2,00,000 analytical professionals in the next three years. Even in the US, only 40 out of 100 analytical professional positions can be filled”

Data analytics professionals are primarily statisticians, mathematicians, data warehouse /database engineers, data miners and IT professionals with data warehousing skills.

A data scientist is a hybrid of many of the above-mentioned skills and therefore they called rare breed. To meet their talent requirements, some companies have developed unique programmers.

US-based thought leader and HR consultant, Jason Averbook, said: In addition to math and statistics, there is also a requirement for people with marketing communications. It is this combination of math and marketing communications that will create storytellers so that the data can be used and be a story. The entire science/data analysis area is undergoing a major transformation right now.

Averbook, Who recently was in India as a keynote speaker at SHRM Tech HR, told TOI that companies should hire new students. “Twenty-year-olds are much more skilled in data than forty-year-olds, and the sooner companies can get their hands on those who really understand the data and then teach them business requirements.

Conclusion

However, talent also needs to be built from within through re-skilling. Although organizations are preparing existing analysts and senior managers with analytical skills for the roles of data scientists and building the talent pool at home, advanced analytical skills are not easily learned.

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