Over the past five years, enterprises have experienced an acute talent shortage for positions involving data analytics. As data proliferates, using it as a competitive advantage for business decisions, automation, and research and development has likewise become higher and higher priority for organizations. The workforce, however, lagged several years behind demand in large part because of the four-year university cycle and lag on the parts of schools themselves to offer majors and classes in computer science and data science.
Based on a survey deployed to 1,000 enterprise recruiters for high-tech analytics roles at companies including Square and Goldman Sachs, this trend appears to be reversing for 2019 and 2020, though. 76% of recruiters said that the supply of qualified college graduates for analytics roles has increased by 20% or more from 2016 to now/ for 2020. NewtonX investigated how this flood on the supply side will affect salaries, demand, and the role of data analytics for enterprises over the next five years.
Millions of Workers For Millions of Data Points: The Changing Role of Data Analytics in Enterprise
Traditionally, analytics jobs require years of experience in niche subject areas (machine learning for specific architectures, for instance), and the majority of demand for these positions came a few large tech companies (think: Google, Amazon, Facebook, etc.). However, as enterprises have begun to leverage data analysis across industries and business applications the field has opened up to generalists and recent college graduates who have foundational skills in the space but are not specialized or senior.
In response to this shift, more and more students and job seekers have pivoted into data science, attracted by the allure of high salaries and engaging work. It’s not uncommon for seed-funded or Series A startups to have multiple data scientists on their teams, often people with only a few years of experience or a master’s degree under their belts.
The result? Almost 40% more qualified data scientists and data analysts in 2020 than there were in 2016.
How The Workforce Boom Will Affect Non-Tech Enterprises
As we recently wrote, these days even most non tech companies are still tech-first — meaning, legacy industries such as banking and healthcare have transformed to leverage data, analytics, and AI for critical business processes. These industries stand to gain the most from this employment boom. Their needs are less specialized than true tech companies, and with the proliferation of ancillary analytics training programs such as bootcamps and one-year master’s programs a more diverse set of candidates will emerge (such as MDs trained in one-year machine learning programs).
Because of this new abundance of talent, enterprises will no longer be subject to the same level of competition with tech companies. The insurance industry and banking industry are likely to see the biggest benefit from this change — they will attract data analytics talent without having to go head to head with Silicon Valley perks and salaries.
The Effect on Talent: How Being a Data Scientist Will Change
Now that the discrepancy between demand and supply of talent is closing, hiring practices and salaries will reflect this. By 2025 it will become less common for recent graduates to be snatched up at astronomical salaries with little-to-no job experience. In much the same way that coders shifted from being incredibly rare to being much more common after the proliferation of coding academies, analytics workers will now become more accessible.
That said, demand will not decrease as a result of this change in supply — in fact, as data continues to proliferate, companies are expected to invest even more heavily in data analytics and science.