All this while, it was common knowledge that the growing need for Data Science talent is burgeoning to levels that that supply is unable to match. Great Learning's in-depth study into the trends when it comes to hiring in the domains of Analytics and Data Science has shown that this is not an isolated case, a staggering 92 per cent of hiring managers have attested to this ever-widening gap which will continue to widen unless there are massive efforts to upskill. "Greater partnerships between academia and industry are crucial to bridge the gap," stressed Hari Krishnan Nair, Co-Founder, Great Learning.
But the question remains, in what ways can higher education gear up to nurture such talent in students? Nair believes that a revamp is already underway but a continuous one is the need of the hour, to ensure that the curriculum is in tandem with the industry development and needs at all times. But the first challenge that he would like to see addressed is the lack of skilled faculties with industry-ready knowledge. "It is of utmost importance that teachers in fields like Artificial Intelligence, Analytics and Data Science undergo training and upskill to deliver quality world-class education. Industry experts, mentors and experienced professionals must also be consulted to curate a more updated and industry-relevant curriculum." Practical aspects of any subject are also equally important, thus, he explains that, "Employers nowadays expect freshers to possess domain-specific knowledge like product and service advertising, data analytics, web and mobile app development and spreadsheet skills. Cognitive skills like reasoning, analytical thinking, complex problem solving, active learning and critical reasoning also play a deciding factor for recruiters."
Those who pull their weight
As far as training goes, universities, corporations and even EdTech players are pitching in to hone Data Science talent. Taking the case of Great Learning themselves, they inform us that courses like Post Graduate Program in Data Science and Business Analytics and Post Graduate Program in Data Science and Engineering have become quite a hit. As a result, over 600 organisations hire through them. But students, here's another point worth noting. Specific knowledge of a given data science function will no longer suffice. Organisations need you to go beyond. So brush up your unique datasets and implementations within the industry for a bright career in the field of Data Science. Also, 22 per cent of hiring managers still look at referrals as far as hiring is concerned, so start setting good impressions folks!
Digging deeper into the study, it states that emerging skill gaps within Data Science exist specifically in areas like NLP (Natural Language Processing) (15 per cent), Artificial Intelligence (AI) (12 per cent), robotics and automation (11 per cent), Machine Learning (ML) (7 per cent) and a whole lot more. That's because these functions are emerging as professional competencies across domains as an authority to drive business solutions. "For instance, NLP has been increasingly adopted by banks to automate document processing, document analysis and customer service activities. This skill is also useful in the e-commerce industry to make search results intuitive and analyse customer voice calls and emails. Similarly, AI is increasingly adopted across industries, including digital media, streaming, advertising and technology (software and hardware). Robotics and Automation are utilised across industries to develop chatbots that automatically converse with customers and resolve some level of customer complaints. These chatbots have seen increased applications in customer service functions in BFSI, e-commerce and telecom service providers, among others. Moreover, Automation as a function is witnessing greater application to suffice routine applications, such as invoice processing and document handling, in the industries of telecom, FMCG, BFSI and retail," Nair points out.
Hackathons are the way to go
Coming back to where specifically the skill gap exists, there are two aspects — about 57 per cent of the hiring managers note that this gap exists at the entry-level while 27 per cent are of the opinion that even at the mid-level roles, meaning with team leads and project managers, can also do with some brushing up. When it comes to the former, hiring via hackathons seems to be the best bet. "Organisations invest in new-age hiring tools to assess candidates’ problem-solving approaches. Hackathon activities allow the recruiters to gauge if applicants are team players and can collaborate with cross-functional teams to finish the given task effectively. It also helps them to efficiently recognise individuals who show a knack for innovative and creative thinking. Hackathon techniques are further utilised to help identify the suitable candidate for a specific function by offering them a business use case to come up with tactical solutions. Top candidates who design unique sustainable and viable business strategies are then selected for subsequent rounds of screening and evaluation," highlights Nair adding that Dish Networks, Mathworks, HDFC Life and other organisations have already collaborated with Great Learning for organising these events.
If there is a skill gap, then there is a glaring gender gap as well and 68 per cent of hiring managers have agreed to this fact. But don't despair yet, as in the last five years, there has surely been an upswing as far as increased participation and involvement of women in Data Science is concerned. "Improved workplace and recruitment policies by corporates, equal growth and pay opportunities, growing learning avenues are a few elements that can pave the way for the entry of more women in the sector," explains Nair and adds that they have also tied up with leading corporates to improve diversity in the workspace. Another interesting statistic the study threw up is that Bengaluru is the preferred destination for 54 per cent of hiring managers while 15 per cent show faith in the talent pool from Hyderabad.
