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Business EconomyPosted at: Oct 19 2021 4:13PM


92 percent hiring managers witness massive supply gap: Study

Bengaluru, Oct 19 (UNI) A study on the hiring trends in Analytics and Data Science domains conducted by Great Learning, India’s leading EdTech Company for professional and higher education has revealed that the industry is witnessing a massive supply gap when it comes to Data Science talent, with 92 per cent hiring managers having faced the shortfall.
The study also flags emerging skill gaps in Data Science specialist skills like NLP, Artificial Intelligence Robotics & Automation, Machine Learning and so on.
As a strong endorsement of the growing mainstreaming of the Data Science domain, close to half of the surveyed hiring managers consider a formal qualification/degree in Data Science to be essential for a career in Data Science.
The study also finds that the lack of gender parity is an issue in the Data Science domain, like it is with the broader tech domain.
With the hiring activity coming back to pre-pandemic levels, the report captures a number of insights on hiring trends, demand for talent, skill gaps and other challenges in hiring.
A little over half of the surveyed hiring managers represented B2B enterprises, about 1/4th represented B2C companies and the rest included Government and others. Industry sectors like BFSI had the maximum representation (21 per cent) followed by IT/ITES, Retail, E-commerce, Telecom, Engineering and Manufacturing.
As per the study, a wide gap exists between the talent sought by enterprises and the supply that the vast talent pool offers.
Of all the hiring managers and leaders surveyed for this study, 92 per cent confirmed that they have witnessed a wide demand and supply gap between Data Science talents in India.
57 per cent believed that the gap between supply and demand exists at the Entry Level/Fresher level while 27 per cent of the hiring managers believe that the talent gap exists in the mid-level roles of Team Lead and Project Management, highlighting the need to upskill both early stage and mid-career professionals with enterprise-specific use cases of Data Science.
The biggest skills lacuna was identified in the area of Natural Language Processing (NLP) by 15 percent of the hiring managers followed by Artificial Intelligence (12%), Automation (11%), Computer Vision (CV) (10%), Analytics (9%) and Machine Learning (7%).
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