We have entered a new technology age. One of machine learning aided by human expertise. This brings into the picture a whole avenue of new technologies and completely new job roles.
One of the primary topics I hear in daily conversation with colleagues is how challenged teams are with newer machine learning technologies. This could represent shortcomings in several areas, including lack of resource availability or lack of individuals skilled in the particular area of machine learning.

The Opportunities Abound

Let’s explore this in some detail. Machine Learning represents one of the largest growth opportunities for the next decade. There is a great summary of this in a Forbes articles by Louis Columbus entitled, LinkedIn’s Fastest-Growing Jobs Today Are In Data Science And Machine Learning. In this article, he summarizes some key findings from LinkedIn’s research:
  • Machine Learning Engineers, Data Scientists, and Big Data Engineers rank among the top emerging jobs on LinkedIn.
  • Data scientist roles have grown over 650% since 2012, but currently, 35,000 people in the US have data science skills, while hundreds of companies are hiring for those roles.
  • Job growth in the next decade is expected to outstrip growth during the previous decade, creating 11.5M jobs by 2026, according to the U.S. Bureau of Labor Statistics.

The Skills Are in Short Supply

So we’ve established that the opportunities are ripe for this field. What about the skills?
Based on the availability of job openings and difficulty in finding candidates to fill these positions, it indicates there is a large skills gap. Per MIT’s article by Tom Relihan, Machine Learning Will Redesign, Not Replace, Work, the issue can be summarized as follows:
It’s time to shift the conversation around AI and machine learning from threats of job replacement to opportunities for job redesign.
What does this mean? It means that even though machine learning may be taking over tasks performed by humans, it is opening up a whole new field of jobs that previously never existed.

How You Can Turn This Challenge into an Opportunity

Now let’s address the opening concern – how do you as an employee or someone that has just lost their job step in and fill that skills gap? You can re-skill and pursue training in the technology areas that support machine learning.
  • Are the jobs challenging and cutting edge? – yes
  • Will you need to demonstrate self-discipline and creativity? – yes
  • Will you have opportunities to show initiative? – yes
  • Is there upward mobility? – yes
  • Is the work and salary rewarding? – yes
  • Is a college degree mandatory? – no
You may have read that last point and thought, wait, what…no degree in this field is needed? Sure a degree is valuable, but the availability of skills in these areas are so short that quite often no degree is needed if you have the necessary skills. How do you acquire those skills, you ask?
Let’s take IBM’s New Collar program, for example. This program identifies multiple job opportunities, covering some machine learning development topics as well as several others. many of these categories align to entry levels in this space focused on skills, not degrees:
  • Application Developer
  • Systems Administrator
  • Data Center Technician
  • Project Manager
  • Software Engineer
  • Designer
  • Technical Support Representative
  • Security Analyst
  • Help Desk Agent

Seize Your Future and Never Stop Learning

So, what if you have no technical background or worked previously in an area that wasn’t even remotely related to these topics? That’s not a problem; it is an opportunity. You can get started easily with technical training, many of which are free, and earn verifiable digital credentials that prove your skills progression as you learn.
Don’t wait. Start turning these challenges into opportunities and change careers to one of the hottest growth areas for the near future. Personally, I am constantly re-skilling and learning new things at least on a weekly basis to stay ahead of the technology curve and I hope to work with you one day in one of these fields.