According to IBM, finding and hire staff with the right mix of skills and experience is a laborious process. About 69% of organizations struggle to recruit quality candidates, according to Accenture research.
âGood data scientists are good at solving word problems,â said Nitesh Shende, chief data scientist at Porter. He said most data scientists struggle to place machine learning models in a business context. “The ability to identify where and what data science techniques to use will only come through case studies,” Shende said.
We took a look at the Computer Engineering and AI and Data Science Courses curriculum in India, and found that most universities and institutions are limited to basic technical skills and lack commercial components.
For example, Department of Computer Science and Engineering at IIT Delhis teach technical subjects and soft skills, but no specific modules focusing on vocational skills or case studies. On the other hand, NYU Computer Courses have a “launch pad” and “keystone of entrepreneurship” projects dealing with business development and hands-on learning
What is the solution ?
To bridge the gap, tech giants Google, IBM, Microsoft, and AWS, along with overseas universities, are offering online certification courses, training, remote management programs, and more. For example, Google offers Grow with Google for professional training and an opportunity to network with top employers.
Likewise, the IBM Professional Certificate Course in Data Science (on Coursera) includes a series of hands-on labs in the IBM Cloud, teaching practical skills.
India has about 4,282 engineering institutes and every year nearly one million engineering graduates enter the labor market. Among which, IT has the highest numbers, followed by mechanics, electronics, civil and electricity.
Nearly 127 degree institutes and 663 undergraduate colleges offer specialized courses in AI, data science, analytics, blockchain, machine learning and robotics â accounting for 10% of the total number of engineering institutes in India, All India Council for Technical Education (AICTE) data showed.
Today, engineers, statisticians, economists and mathematicians are not the only ones entering the world of data science and analytics. Data science is touted as the most in-demand role in 2022. According to the Monster Annual Trends report, 96% of companies are planning or are likely to hire new staff with relevant skills to fill data science and analytics roles in 2022.
Most talk today is about how to apply technological knowledge in a business context. It is essential that colleges and universities prepare students to solve real-world problems. Therefore, introducing âbusiness case studiesâ into the undergraduate curriculum can make a huge difference.
“I could apply for a data science job and if I don’t mess up my resume with all the right buzzwords, I’ll never see a hiring manager,” he said, adding that the whole of the process was interrupted. “Great talents are constantly being eliminated,” he added.
He suggested that recruiters hire junior scientists and hone them. For high-level talent, they have to manually read resumes and create a process to hire them quickly. âPhone screen. One hour interview. Train leaders to hire and help them set up a process,â Vashishta said.
He said: âCompanies hiring tech talent need to realize that it’s not 2012 anymore. Talent assessment is complex and those empty chairs are going to bankrupt your business. Adapt or die.
Jordan Luxfordartificial intelligence recruiter, NLP specialist and host of “The NLP Zone” podcast, said: “Many companies require a master’s degree or higher for their technology vacancies, regardless of the candidate’s experience, and other companies don’t care about education at all.”
“I fully understand the benefits of having a master’s or doctorate in technical roles, but I’ve also worked with some of the best candidates who haven’t gone down the traditional education route,” Luxford said.
He said it is important to have a standard, but companies need to be flexible. Companies will miss out on natural and gifted talent who started working at an early age and therefore chose not to pursue an education, he added.