While the world is still recuperating from the pandemic, businesses, large and small, which banked on technology, were able to move on quickly with their operations. This has led to a rise in demand for tech-based job roles such as data analyst, data scientist, cloud architect, and security engineer, among others. The year 2021 is set to drive massive growth for such roles as organisations are looking to create a skilled talent pool for a better digital continuity. For those of you looking to ride the digital wave and make the best of this situation, equipping yourself with new-age skills is the key to powering ahead in your careers. If you are interested in building a career in information technology, here are the top skills you must have on your wish-list while selecting your course post-class 12.

Research has found that inadequate access to skilled talent, technology, and data is holding back AI initiatives. Most organisations are fully invested in AI but more than half don't have the required in-house skilled talent to execute their strategy, according to new research from SnapLogic. The study found that 93% of US and UK organisations consider AI to be a business priority and have projects planned or already in production. However, more than half of them (51%) acknowledge that they don't have the right mix of skilled AI talent in-house to bring their strategies to life. Indeed, a lack of skilled talent was cited as the number one barrier to progressing their AI initiatives, followed by, in order, lack of budget, lack of access to the right technology and tools, and lack of access to useful data.

AI is not a silver bullet, but the technology can positively impact different sectors in a number of ways. Most organisations, as a result, are fully invested in AI, but they are hampered by a lack of AI skills. In fact, more than half don't have the required in house skilled talent to execute their strategy, according to new research from SnapLogic. The study found that 93% of US and UK organisations consider AI to be a business priority and have projects planned or already in production. However, more than half of them (51%) acknowledge that they don't have the right mix of AI skills in-house to bring their strategies to life.

Previously published on LSE Business Review. Machine learning is poised to pave the way for many exciting opportunities for businesses, but there are many hurdles to be crossed before getting to the finishing line. Many organisations are still struggling with legacy systems and are slow to invest in more advanced technologies. But the more pressing issue at hand, one that has been an ongoing problem for the technology sector, is the short supply of qualified talent to match what is a fast-moving and demanding industry. By design, machine learning is experimental and often unpredictable – a lot of exploration is required before organisations can even begin to make sense of the data and which machine learning algorithms will work best. While the unpredictable nature of machine learning is understandably daunting, many organisations have yet to fully grasp what is required to effectively deploy and manage it.

Machine learning is poised to pave the way for many exciting opportunities for businesses, but there are many hurdles to be crossed before getting to the finishing line. Many organisations are still struggling with legacy systems and are slow to invest in more advanced technologies. But the more pressing issue at hand, one that has been an ongoing problem for the technology sector, is the short supply of qualified talent to match what is a fast-moving and demanding industry. By design, machine learning is experimental and often unpredictable – a lot of exploration is required before organisations can even begin to make sense of the data and which machine learning algorithms will work best. While the unpredictable nature of machine learning is understandably daunting, many organisations have yet to fully grasp what is required to effectively deploy and manage it.

Free catered lunch and a dog-friendly office are two of the perks offered by an educational technology company in Palo Alto, Calif., that's looking to hire a machine learning engineer. The position, posted on Dice, will pay between 140,000 and 160,000 to the right candidate who's skilled in machine learning platforms as well as data mining, statistical modeling, and natural language processing. Job-seekers who possess those skills typically could expect multiple job offers, says Matt Leighton, director of recruitment at Mondo, which specializes in digital marketing and technology staffing. The job titles vary from company to company; some might post positions in search of a data scientist or machine learning engineer, others might be after a natural language processing (NLP) programmer or cognitive computing engineer. But hiring companies are seeking the same talent: "They're people who create algorithms through code that allow computers to self-learn," Leighton says.

Job-seekers who possess those skills typically could expect multiple job offers, says Matt Leighton, director of recruitment at Mondo, which specializes in digital marketing and technology staffing. But hiring companies are seeking the same talent: "They're people who create algorithms through code that allow computers to self-learn," Leighton says. Another area that's driving demand for skilled talent is virtual reality. Demand for machine learning experts and virtual reality pros is spiking as enterprise adoption of these technologies grows.

Free catered lunch and a dog-friendly office are two of the perks offered by an educational technology company in Palo Alto, Calif., that's looking to hire a machine learning engineer. The position, posted on Dice, will pay between 140,000 and 160,000 to the right candidate who's skilled in machine learning platforms as well as data mining, statistical modeling, and natural language processing. Job-seekers who possess those skills typically could expect multiple job offers, says Matt Leighton, director of recruitment at Mondo, which specializes in digital marketing and technology staffing. The job titles vary from company to company; some might post positions in search of a data scientist or machine learning engineer, others might be after a natural language processing (NLP) programmer or cognitive computing engineer. But hiring companies are seeking the same talent: "They're people who create algorithms through code that allow computers to self-learn," Leighton says.