Data Translators A Big Draw As Companies Make Shift To Large Scale AI

With a shift to large scale artificial intelligence (AI) implementation, organizations are seeking data translators to interface between the management and data scientists effectively. They are investing more in building a talent pool with people from mathematical and statistical backgrounds.

Even though the data boom is relatively a recent phenomenon, around 90 percent of the world’s data has been generated in the past two years only. However, in terms of usage, firms have only been able to scratch the surface by harnessing less than 1 percent of those to extract useful insights. Benefits from AI largely depend on how well the data scientists can model the algorithms (rules) to find trends across millions of data sets, and these interpreters can provide useful insights into data modeling.

Even when the algorithms are perfect, it may not suit the business needs of a company, and this is where the translator fills in.

“Although it is too early to provide data, there has been a definite spike in hiring of people with mathematics and statistics background. Whether it is BFSI, healthcare, IT & ITeS, engineering, tourism, agriculture or government, almost every field requires handling and interpreting data and predicting real-world problems and providing modeling outcomes,” said Mayur Saraswat, head of digital, IT & telecom vertical, Teamlease Services.

The expertise and skills required definitely has an underpinning with training in mathematics and statistics, he added. The current demand is led by the e-commerce segment, including FMCG/FMCD companies, where the demand for business analysts to understand buyers’ behavior is high.

There has also been an increase in demand for these competencies in technology start-ups and AI/analytics companies that are ramping up the requirement for data scientists, along with IT consulting and services companies, noted Teamlease.

AI applications have moved from pure-use cases to actual implementations in various areas as companies seek to utilize the boom in data creation in the country.

For example, telecom providers like Vodafone have been using these data interpreters for a few years now to generate insights into different monetization strategies and tariff plans, said sources in the know.

This is a slight shift from the business analyst roles, which are filled by people from technology or engineering background. Firms are also partnering premier institutes like Indian Statistical Institute (ISI) to ensure that their employees are trained in these skills, as AI modeling is in big demand among businesses.

“Pure research in maths, data sciences and economics, among others, have become high demand areas but there is a need to convert these people into data modellers and scientists. We have tied up with NIIT to create a curriculum and case studies for a two-year training programme for experienced professionals from maths and statistical backgrounds,” said Keshav Murugesh, group chief executive officer (CEO) WNS Global Services and vice-chairman, Nasscom. The company is already exploring similar programmes with other institutions to ensure a strong supply of data modeling and interpretation professionals.

“We engage with premier institutions, such as the ISI, to hire new candidates from campus. We are also collaborating with the institutes to organize intensive training programmes to enhance skills of our existing employees,” said Sanjay Jalona, CEO & managing director of midsized IT services company LTI.

LTI also conduct Hackathons to identify potential candidates with mathematics, statistics and data engineering backgrounds who showcase these traits. It works with the start-up community to engage and solve problems that require extensive research orientation in mathematics and statistics.

Analysts suggest that for every data scientist, companies will need five to seven data engineers and around 10-15 translators.—Business Standard