Is data science still a growing field in Malaysia in 2023 and beyond? Isn’t artificial intelligence (AI) the in-thing now?
Here’s the answer you’re looking for:
Businesses and society are only producing more and more data every day, with no signs of slowing down.
Still, one of the most popular questions we get asked at Forward College is, “How much does a data scientist earn?”
But before we discuss the various data science roles and their salary ranges in Malaysia, let’s briefly talk about why data science careers are so attractive in Malaysia.
If you feel like everyone around you is trying to pursue a data science career, you’re not hallucinating.
It’s actually happening.
The reason is that many working professionals suddenly found themselves needing data skillsets. Be it whether you work in finance, E-commerce, or manufacturing, there was suddenly a need to collect, analyze, and build models out of data.
Few more reasons here:
Growing Demand: Companies across different industries are now seeing the advantage they get from making data-driven decisions. And so the demand for data scientists grew as companies needed to get their analytics and prediction analytics game up to speed.
Competitive Salary: Because the demand for data scientists has gone up, so has the salaries, making it an attractive career for many working professionals. Adding data science skill sets will also help them progress in their careers.
Government Support: Government bodies like Malaysia Digital Economy Corporation (MDEC) have been pushing for the upskilling of Malaysians in the areas of big data, data science, and AI from as early as 2015.
Diverse Industries: Because we have a diverse economy here in Malaysia – spanning from finance, E-commerce, healthcare, and manufacturing, there are plenty of job opportunities for data scientists.
Work-life quality: Another reason that attracted many individuals to consider a data science career in Malaysia is that they believe data scientists have a better work-life balance, compared to software engineers.
However, from our experience, that usually depends on the company you work for, rather than the role.
Media: And of course, not forgetting the media. If you’ve been researching about being a data scientist – you’ve probably come across the phrase “Data is the new oil”
The quote was actually coined by Clive Humby, a British mathematician in 2006. But it was only in 2017 when the Economist published an article titled “The world’s most valuable resource is no longer oil, but data” that the phrase started drumming up lots of interest.
Ok, let’s talk about some data science roles and the salary range you can expect.
You will find that there are many roles in data science. And their responsibilities often overlap each other.
That said, here are the common data science job roles, what they do, and the salary range to expect in Malaysia.
A data analyst is responsible for collecting, cleaning, and analyzing data to extract insights to help organizations with decision-making.
For example, an E-commerce data analyst tracks user behavior, website traffic, and customer reviews to make a decision about which product the company should continue selling and which they should drop.
The skills needed as a data analyst are statistics, mathematics, and programming – which involves tools like Python, MATLAB, and more.
Career progression for a data analyst includes becoming a data specialist, senior data analyst, research analyst, and analytics manager.
A data engineer builds and maintains systems that collect and store data. Data engineer roles are usually more technical, compared to data scientists.
Most organizations have custom data models and legacy systems to be wrangled. That makes data engineers a very crucial part of the data science process. Without the existence of good data engineers to ensure proper data collection and structuring, the promises of machine learning and predictive analytics will never be realized.
The skills you need as a data engineer range from SQL, data warehousing, software engineering, and mainly database management.
As a data engineer, your career progression would be climbing up the ranks to be a senior data engineer, lead data engineer, or data engineer manager.
Data scientists were touted as the sexiest job of the 21st century, because of the sudden rise in demand a few years back. That said, it still is a very attractive job today.
Even as a junior or entry-level data scientist, depending on where you work, you can expect to ask for a salary of RM5,000 or more.
Data scientists are responsible for developing and applying data-driven solutions to business problems. They usually also work with product, sales, and marketing teams. Then using tools like SQL, Python, and R, they build models to make predictions or recommendations.
Many industries, from oil and gas, E-commerce to consulting are actively hiring data scientists in Malaysia.
The natural career progression as a data scientist is to move into senior positions like a senior or chief data scientist, which brings us to the next job role.
A senior data scientist is simply a more experienced data scientist. This role might involve leading and mentoring a team of data scientists to develop and implement data science strategies for an organization.
Companies offering senior data scientist roles in Malaysia usually require the candidate to have at least 3+ years of experience working in data-related fields related to analytics and applied data science.
Like an architect, a data architect is in charge of designing the overall data strategy for an organization. This could be for the company internally or for a client as well.
A data architect needs to be well-versed with the knowledge of systems development, and project management approaches, including design and testing techniques. This includes having a good grasp on data models, database development standards, implementing and managing data warehouses and analytics systems.
Most data architects are usually data engineers first, and therefore they possess a good command of programming in a few languages.
There’s a range of career pathways for a data architect, including moving up into chief information officer or IT management roles.
While what a machine learning engineer does, closely relates to what data scientists do, it’s more of an engineering role that focuses on machine learning.
A machine learning engineer will be more focused on production and software engineering. Data scientists on the other hand focus a lot on presenting and working with stakeholders.
Plainly put, machine learning engineers bridge the gap between software engineers and data scientists, where typical software engineers may lack skill sets in statistics and data scientists may lack deep software engineering skills.
The machine learning engineer career path is one of the most desirable career paths in data science. From here, they could progress to be an NLP scientist or a head of AI.
The data science field is wide, especially in Malaysia where there is still plenty of potential for growth and job opportunities.
While we did our best to find the current salary ranges for each of the data science roles above, take note that salary ranges are usually subjective, and depend on the companies hiring and your skill sets.
At Forward College, we help students pick up data science and find their dream data science jobs.
If you’re ready to start, consider enrolling into data science essentials, our beginner-friendly data science program for students and working professionals.