All the while, it was common knowledge that the growing need for data science talent is increasing to levels this supply is unable to match. Great Learning’s in-depth study of hiring trends in analytics and data science showed that this is not an isolated case, 92% of hiring managers have attested to this ever-growing gap which will continue to widen unless there are massive efforts to improve skills. “Greater partnerships between academia and industry are essential to bridge the gap,” said Hari Krishnan Nair, co-founder of Great Learning.

But the question remains: in what ways can higher education prepare to develop such talent in students? Nair believes an overhaul is already underway, but an ongoing overhaul is the need of the hour, to ensure the program is in tandem with the development and needs of the industry at all times. But the first challenge he would like to see taken up is the lack of qualified faculties with industry-ready knowledge. “It is of the utmost importance that educators in areas such as artificial intelligence, analytics and data science receive training and development to deliver world-class quality education. Industry experts, mentors and experienced professionals should also be consulted in organizing a study program. “The practicalities of any subject are equally important, as well,” he explains, “employers Newcomers today expect newcomers to have domain-specific knowledge such as product and service advertising, data analysis, web and mobile application development, and spreadsheet skills. Cognitive skills such as reasoning, analytical thinking, complex problem solving, active learning and critical reasoning also play a decisive role for recruiters. “

Those who pull their weight
With regard to training, universities, companies and even EdTech players are mobilizing to develop talents in Data Science. Taking the case of Great Learning themselves, they inform us that courses like the Graduate Program in Data Science and Business Analysis and the Graduate Program in Data Science and Engineering have become successful. As a result, more than 600 organizations are hiring through them. But students, here’s another point to note. A specific knowledge of a given function in data science will no longer suffice. Organizations need you to go above and beyond. So refresh your unique data sets and industry implementations for a successful career in data science. Plus, 22% of hiring managers always review referrals when it comes to hiring, so start creating good impressions!

Looking further into the study, he indicates that emerging skills gaps within data science exist specifically in areas such as NLP (natural language processing) (15%), artificial intelligence (AI). (12%), robotics and automation (11%), Machine Learning (ML) (7%) and much more. This is because these functions emerge as professional skills in all fields as the authority to drive business solutions. “For example, NLP is increasingly adopted by banks to automate document processing, document analysis and customer service activities. This skill is also useful in the ecommerce industry for making search results intuitive and analyzing customer voice calls and emails. Likewise, AI is increasingly adopted across all industries, including digital media, streaming, advertising, and technology (software and hardware). Robotics and automation are used across industries to develop chatbots that automatically engage with customers and resolve some level of customer complaints. These chatbots have seen their applications increase. in customer service functions at BFSI, e-commerce and telecommunications service providers, among others. In addition, automation as a function is finding greater application to suffice for routine applications, such as invoice processing and document management, in the telecommunications, FMCG, BFSI and retail industries ”, emphasizes Nair.

Hackathons are the way to go
Getting back to where the skills gap exists, there are two aspects – around 57 percent of hiring managers note that this gap exists at the entry level while 27 percent believe that even at mid-level positions, meaning with team leaders and project managers, can also be the subject of a refresh. As for the former, hiring through hackathons seems to be the best bet. “Organizations are investing in next-generation recruiting tools to assess candidate problem-solving approaches. Hackathon activities allow recruiters to assess whether candidates are team players and can collaborate with cross-functional teams to complete the given task effectively. It also helps them effectively recognize people who demonstrate a talent for innovative and creative thinking. Hackathon techniques are further used to help identify the right candidate for a specific role by providing them with a use case. The best candidates who design unique, sustainable and viable candidate business strategies are then selected for subsequent screening and assessment rounds, ”says Nair, adding that Dish Networks, Mathworks, HDFC Life and other organizations have already collaborated with Great Learning to organize these events.

If there is a skills gap then there is also a glaring gender gap and 68 percent of hiring managers agreed to this fact. But don’t despair yet, because over the past five years there has surely been a pick-up in the increased participation and involvement of women in data science. “Improved employment and recruitment policies by companies, opportunities for growth and equal pay, increasing learning paths are some elements that can pave the way for more women to enter the sector,” explains Nair and adds that they have also partnered with companies to improve diversity in the workspace. Another interesting statistic cited by the study is that Bengaluru is the preferred destination for 54% of recruiters, while 15% trust Hyderabad’s talent pool.