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State of Data Science & AI Skills in India – Data and the Art of Smart Intelligence

Riding on the positive spending growth trends in AI, there has been a spurt in the demand for professionals which has doubled in the past 3-5 years. The surge in demand for Data Science & AI professionals in India can be attributed to a combination of favorable factors - a young trainable population that can be upskilled, demand for talent with Digital skills, and an increasingly data driven culture at end user organizations. Supportive government initiatives, particularly around skill development is also helping. Future Skills Prime, a partnership between MeitY & NASSCOM, is a skilling ecosystem focused on emerging technologies, which aims to reskill/upskill about ~ 2 Mn professionals. Led by the Draup platform, an analysis was performed to ascertain and measure India’s AI/ML BDA tech talent across various job roles, locations, and technologies.

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Key Findings

India has the 2nd largest AI/ML/Big Data Analytics talent pool globally

  • India ranks 1st in terms of AI skill penetration with a score of 3.09 and has also recently secured the 1st and 5th ranks in A talent concentration and AI scientific publications, globally.
  • Has an installed talent base of 416K professionals (as of August 2022) and a current demand of ~629K
  • However, the current gap between demand and supply is about 51
  • By 2026, the estimated demand for professionals in India is expected to be over 1 million.
Multiple factors joining to push demand northwards

  • Impacted by the generation of big data across enterprise value chains and the integration of AI/ML technologies in Big Data/Data tools and applications
  • Proliferation of pre trained ML models on the cloud and the push towards automation is changing the landscap
  • Higher than average compensation and growth prospects.
  • The demand for skills cuts across industry verticals %
  • Growing share of Digital talent as a percentage of overall tech talent is the new trend. Companies are realigning their businesses based on talent needs of the future.
5 Critical Roles in Demand

  • Certain roles have a higher degree of demand supply disparity, ranging between ~60% and 73% - ML Engineer, Data Scientist, DevOps Engineer and Data Architect.
  • 75 - 80% of the job openings fall between 0-5 years and 5-10 year experience bands
Transitioning to DS&AI roles depends on multiple factors

  • The proliferation of freely available tools and platforms (e.g. Google/Kaggle) is fast-tracking the growth of a large developer community and associated ecosystems
  • 33% of India’s DS&AI developer talent is between 18 and 21 years of age.
  • The time taken to pivot to DS and AI roles may range between 3 months to 7.5 months and 5.5 to 10.5 months respectively depending on base starting roles.
  • Data Analyst, Software Engineer, Application Developer are observed to have a higher transition propensity.
Key recommendations to maintain India’s edge in AI talent

  • New Education Policy (NEP) – To ensure a quality pool of AI talent that is technically sound and industry read
  • Reforming Primary & Tertiary Education – To ramp up primary & Tertiary teaching infrastructure to capitalize on opportunities. Adding multidisciplinary curriculum and research impetu
  • Improving employability – To reduce the disconnect between curricula and industry demand via stronger industry academia tie ups and collaboration
  • Improving Post-doc Research in AI – To nurture AI talent at the Doctoral level and providing research opportunities

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