6 Biggest Tech Job Myths In Malaysia You Need to Stop Believing
The year 2020 has thrown many companies off their balance. But, there’s a silver lining! While our economy took a hit and many jobs were lost–there was a growth spurt in the demand for tech-based jobs.
If you’re someone highly passionate about technology and want to secure a rewarding job in the tech industry, what should you expect? Do we have to work all day as web developers? What is the kind of salary you should expect? A common misconception for many: having a tech job means having to work in front of a computer screen all day. In reality, that’s not the case. Tech jobs have, in fact, changed over the years.
I’m hoping to help you navigate the tech industry better with this article. Let’s start busting common tech job myths in Malaysia.
Myth #1: Programmers are loners.
This is probably one of the biggest tech job myths about programmers, whether a web developer or software engineer. The truth is, you don’t have to be a loner who spends the entire day from 9 AM to 11 PM writing codes away in a cubicle. While it’s true that programmers often need some alone time to focus on writing codes, programmers typically work on teams that consist of other people, such as designers, product managers, and marketers.
This is where interpersonal skills like collaboration, empathy, and communication come into the job. While a good programmer excels with a strong sense of logic, coding language, and math–great programmers are people who seek to understand users and customers. Because the app or project most companies build is bigger than what a single programmer can handle. We always need teamwork to make the dream work. Don’t let the loner stereotype defer you from entering the tech industry!
While programming and writing codes can be a solitary activity in computer science courses or college, it’s impossible to avoid teamwork in an organizational setting.
Myth #2: You need a computer science degree.
According to many tech company founders, like Andrew Bialecki of Klaviyo–a hyper-successful eCommerce marketing platform with 600 employees, 60,000 customers who recently raised $200 million in series C funding at a valuation of over $4 billion–you don’t need a computer science degree to get into technology.
“I don’t think you need a computer science degree or programming degree to get into technology or to be a software engineer. That’s just not a requirement. Really, what it takes is hard work and lots of practice.”
If you are a fresh graduate, take up internships or apprenticeships with promising companies. As a young professional, it’s better to pick up practical work experience from various companies and verticals, rather than only having a paper qualification to show. Employers are often looking for individuals who can add value to the company. Therefore, having something tangible to show such as a live project, app, website or a recommendation from a past employer brings more weight.
But what if you’re planning a mid-career change into tech? If so, think about going the extra mile and apply to companies with a tech team that would be willing to mentor you on the job. You might have to do more and possibly take a slight pay-grade cut. Think of it as a ‘tuition fee’ to pay for learning. And the topic of pay grades brings us to the next myth…
Myth #3: Malaysian companies don’t pay well.
A quick search on Indeed shows that a junior data analyst in Malaysia gets paid an average salary of RM2,741.
All those years of practice and spending costly college fees for a salary grade like this? While that might discourage you, I’d urge you to look beyond average salaries. What you need to realize is that companies are simply following a standard ‘market salary’, if there is even one, to begin with. But that doesn’t mean you should just accept the salary offered to you. Negotiating your salary is one of the best things you can do for yourself financially. If you find yourself with an opportunity to negotiate, here’s what to do.
First, determine the general salary range for your position (notice I said ‘range’) on sites like Jobstreet, Indeed, and Payscale. Make references of the salary ranges before going for the interview. Next, find out what the company wants. What are the problems they are looking to solve by hiring you? Draft a few plans to solve these problems. Finally, during the interview, ask, ask and ask. Ask the hiring manager about the problems and challenges they face in the company. Then present your plans to solve them and ask for a compensation plan that fits both your side and the company’s side, based on the salary range you’ve researched earlier.
Of course, I’ve simplified the entire process of negotiating your salary. The takeaway–take the active role of presenting yourself as a problem-solver instead of someone just looking for a job. If the company has an RM5 million-dollar problem that you can help solve, how much do you think you’re worth to them?
Myth #4: You need to learn the best programming language.
What’s the best programming language? Which programming language should I learn if I want to go into data science? We get asked these questions almost every day at LEAD. To be fair, the motive behind these questions is because the asker wants to make the best use of their time and effort–learning a programming language that pays back the best dividends.
Programming languages are simply tools. It’s no different than a tool in your hardware box. If you want to fix a pipe, you probably pick up the spanner. And if you want to hammer a nail, you should use a hammer. Yes, it’s possible to use a spanner to hammer a nail, just like how the same programming language can be used to solve different problems. Instead of asking about learning the best programming language, start from the end. What are you planning to do?
Myth #5: You have to be good at math and science.
There’s no denying that mathematics and science are important for some specific tech jobs – like a data scientist or database engineer. However, you’ll find out that most data scientists are not mathematical geeks. This misconception usually comes from the lack of understanding of how data science is applied in business or how real-world coding is usually applied.
In school, the math problems we face almost have a definite answer. You’re either correct or wrong. However, with real-world data science or software development projects, you’re usually looking to solve problems. Any experienced data scientist would tell you that there are many different ways to arrive at a solution.
What truly sets great and mediocre tech professionals apart is problem-solving skillsets. Problem-solving skillsets are needed in most tech jobs, whether you’re a data scientist or backend engineer. But what if you’re interested in areas such as data science, machine learning, and AI – where some higher level of mathematics is needed? This brings us to our next point…
Myth #6: Taking a tech bootcamp guarantees you a job.
Because of the popularity of the tech field, plenty of bootcamps, courses, and certification programs have come about. You don’t have to go far around town before bumping into a college or university ad. Driving around Petaling Jaya (where I live), I’m constantly greeted with digital billboards with ads by colleges and universities – enticing me to get ready for digital transformation and industry 4.0 by taking up tech courses. And with the growing competition amongst colleges and universities, some decided to make bolder claims. So they push harder on their message and we begin to see: “Guaranteed job placements!” “100% job guarantee!” on their advertisements.
These claims are created for the sole purpose of driving student enrolments for their courses. After all, if a job placement is guaranteed, then fees for the course can be seen as a great investment, right? Don’t get me wrong. I’m not discouraging you to take tech courses or bootcamps. But if your main motivation is to just earn a paper certificate, know this. Just like you, hundreds and thousands of others have thoughts about going into the tech industry.
This means you inevitably find yourself in a red ocean of tech candidates. Armed with only a paper certificate puts you into an average quotient. Put simply, in the eyes of the hiring manager – there is slight, if any difference between you and other candidates. So it becomes a race to the bottom. If all candidates are the same, then the company simply looks for the candidate willing to accept the lowest salary.
At the end of the day, even with all these myths busted–it can still be tough to know where to start. Most of the time it is fear that holds someone back from starting; the fear of failing, the fear of getting ridiculed, the fear of starting over again, and more. Something that will help build up your confidence is to be in a community of people who share the same interest and journey as you, leveraging tech workshops such as Data Science Amplify. More importantly, just get started and your journey will become clearer as you go.
You can also break into the tech career with a workshop. We learn stuff by doing things. That’s what a workshop is for. You’ll get to work. It is with deliberate practice, showing up, and allowing yourself to make mistakes – that would get you started with your tech journey. Data Science Amplify is a workshop that helps you level up your career with data analytics.
What’s data analytics for and why is it booming? For one, companies are looking to implement it, so they can make decisions out of their data. What if E-commerce companies could predict the type of products their customers want? They could then create a better user experience. Or what if video-streaming companies (Netflix) can learn the types of movies you prefer watching? The person who helps companies do this is the data analyst. And that can be you.