Consider a Career in Machine Learning
By Hayley Shaughnessy
You might have heard that robots are coming for our jobs… and that it’s even happening sooner than we thought. As in, right now.
In many workplaces, many of us may be questioning whether or not our job is robot-proofed. We may also be searching for ways in which we can protect the human elements of our skillsets, such as emotional intelligence, humour and creativity.
But instead of being on the defensive when it comes to robots at work, why not turn to the offense and seek opportunities?
In fact, there may be more opportunities than we think. Executives at Google have made claims that there will be a boost in ‘machine learning’ over the next few years. There are a few areas in which employees and job seekers can embrace the robots, from project testing to development and engineering, too. After all, machines can always use the tender care from human beings, right?
What is machine learning?
According to SAS, machine learning is “a method of data analysis that automates analytical model building.” In other words, it’s a type of artificial intelligence, or the fuel to the robot engine to ensure work is done effectively and efficiently. It focuses on the development of programs that can easily be changed and customized to new environments and tasks.
Of course, machine learning is considered a buzzword among those working in tech and innovation. But its popularity has grown with the expansion and accessibility of data analytics in various industries as well. Simply put, it’s a major advancement in the way that we work and exist in our local and global economies.
How can you get there?
In order to pave a direct path to machine learning, knowledge and education rooted in computer or applied science is a must. Being well-versed in programming languages such as Python, Java and Scala is a strong asset, though you’ll want to stay informed about industry standards and emerging trends.
Once school is finished, machine learning hopefuls can keep an eye out for job postings such as Machine Learning/Data Engineer or Data Scientist. While on the search for the best fit, aspiring professionals can also further their expertise in coding and big data tools such as Hadoop.
What should you expect?
Entry-level positions in machine learning earn an average of $88,000 USD per year. Those interested in the field can also expect to be continually learning and keeping up with technology advancements and improvements.
Here are a few soft and hard skill pairings to consider for a career in machine learning.
Design and development
As robots are being put in the environments we humans choose for them, such as vehicles, we’re also ultimately in charge of how they are designed and put together.
For those working in development, a lot of time is spent researching and imagining all opportunities that current tech has to offer (or simply new tech, a la Elon Musk of Tesla). Employees in development are able to craft new frameworks and parameters that robots work within. This means using design-type thinking and imagination to help set their limits and potential for completing certain tasks.
Many industries need professionals who can fuse design and development to prepare industries for the future, and that’s where you can come in.
Problem-solving and project testing
Just like humans, robots don’t have the answers to everything (or at least not yet). That’s why problem-solving skills – from people – are still needed in the workplace. As we’re still in the early stages of a ‘robot takeover,’ we don’t have the capabilities for robots to help robots just yet.
When an issue or error arises in the machine learning process, it’s up to the employee to rework and solve the problem so that the robot can complete the assigned task. This can involve trial and error and using critical thinking to come to a solution.
Being an effective problem-solver is a key skill that many employers have long looked for, but if you excel at finding solutions, you may want to consider applying your skills in a project testing role. You have to be willing to think outside the box and try, try again when things (or the robot) aren’t working in your favour.
Intellectual curiosity and innovation
At the time in which machine learning is up and working the way it should be (fingers crossed), it’s always on to thinking about the ‘next big thing’ or innovation to keep humans working alongside robots (as opposed to competing against one another).
Staying curious for your work surroundings and industry remains a critical quality in an employee in just about any industry. It means that you invest time and energy, generally outside of the office, to keep up to date on new concepts, ideas or even people.
And this isn’t specific to one industry. Whether you work in retail, manufacturing, telecommunications or information technology, every industry needs big thinkers who will be able to spot opportunities to create a symbiotic working relationship between employees and robots.
If you find yourself seeking for more or pairing your soft skills with harder skills in technology like it has been laid out here, you may be headed towards a career in machine learning – or perhaps are already there!
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