Finally Answered: How much does a data scientist earn in Malaysia?

Jul 29, 2021

Ever since we started doing webinars and workshops on Data Science, there is always at least one person in the crowd that asks us this, “How much does a data scientist in Malaysia earn?”

We understand that this is indeed a very practical question, especially for those who are looking to venture into data science as a career prospect.

As much as this sounds cliche, like all jobs, if you are only doing it for the money, you will burn out very soon. So before we actually tell you how much a data scientist earns, we will walk you through a little bit about what a data scientist does, as well as the career prospect of this industry.

What does it mean to be a Data Scientist?

There are many other positions related to the field of big data other than being a data scientist, which includes data analyst, data engineers, etc. So what does it mean to be a data scientist?

Think of a data scientists as more of a managerial role, in which you will need to steer your team to process the chunk of data collected, and turn it into meaningful insights that would contribute to the company’s growth.

So other than focusing on the execution and technical part of the job, it is important for you to have great organisation skills to see through projects, paired with good communication skills so you are able to lead the team, while act as an advisor to your stakeholders based on the data found.

If you are interested to know what does a data analyst or data engineer do, you can refer to this infographic below:

Check these videos out:
Data scientist vs analyst
Data scientist vs data engineer

What is the career prospect for a data scientist?

As we further dive into this data era, many people are considering venturing into data science as this seems to be a great prospect for career advancement.

The great thing about learning data science is that it doesn’t actually mean dropping whatever you have been learning or leaving the industry in which you have been working to go someplace else. Many people who are passionate about what they are doing, and want to gain more insights from available data they have on hand, can take up data science.

For example, you work in a hospitality organisation, and you want to further understand what makes your customers come back and what pushes them away, you can collect the necessary data and analyse them to solve your daily problems. Hence, learning data science in this situation would further help you develop a brand new skillset while increasing your value as an asset to the company.

But for the sake of discussing the career prospect of someone with a background in data science, there are two main types of data scientists, which is Type A and B. Type A data scientists (think “Analysis”), are the ones who take up the majority of data scientists. These folks are known to have vast knowledge in the industry they are in, and often do analytical work in order to gain insights that will benefit the organization.

On the other hand, Type B data scientists (think “Builders”) is the stereotypical programming geeks. These folks are incredibly well versed with various programming languages, and work on building tools and frameworks that can organize the data collected and turn it into actionable decisions.

For a layman’s understanding, the creepy pop-up ads like “Products you like” or “People you may know” are built by these Type B data scientists. For a lead data scientist, they usually are from this category and will have the ability to manage and lead type A data scientists due to their added knowledge.

Depending on which type of data scientist you are setting out to be, but often people start out with their data science careers doing more operational work like data mining, data analysis etc.

Later on, with a few extra years of experience, you can venture further into different verticals of data science (eg: manufacturing, research and development etc), and you may move from the more technical and analytical side of things (Type A)  to building models that allows you to interact with your users (Type B).

In terms of a more developmental progression, you can move up the corporate ladder by becoming a senior data scientist, and then later on the lead data scientist. The lead data scientist will have the opportunity to manage your data science team, as well as act as the advisor to the stakeholders based on your findings.

What is the average pay of data scientist in Malaysia?

After elaborating on data scientist as a career, we are here to finally answer your burning question.

According to recent job vacancies, an average entry-level data scientist or even data analyst is offered RM 4,000 – RM 6,000.

If you continue on to venture into this and become a chief data scientist, to which you will be spearheading and managing the team as compared to working on the technical part of things, your salary could potentially go up to RM 100,000.

Again, when you have more experience, paired with other skill set such as management skills, your salary would reflect based on what you have to offer to the company.

What are the key skill sets that would affect the salary a data scientist earn?

In terms of technical skills, one of the most obvious skills that will affect your salary is the programming language you know. According to the O’Reilly Data Science Survey which comprises of 600 respondents from different industries, the top two most in-demand programming languages are Apache Spark and Scala.

However, in general, data scientists who have mastery in as many programming tools as possible does have a significant impact on their salary. So if you are looking to further expand your career, a continuous learning process of various programming tools will definitely be beneficial.

Another very straightforward factor that affects salary is years of experience, specifically in holding data science roles, as compared to plainly data analysis work.

So as a rule of thumb, if you aspire to become a chief data scientist, always look for job opportunities that allow you to build more models as compared to just crunching numbers, as this can lead you in the right direction for further career development.

Through accumulated experience, you get to learn a larger skill set on top of technical skills such as good management skills to lead a team, paired with a good business intuition that steers them to solve problems. With these skills, it will help you contribute to your organisation more holistically which of course translates your value through the salary they are willing to offer you.

Job demand for data scientist and data professionals in Malaysia in 2021

Data science will still be the most highly in-demanded skill moving into 2021, it was even rank by #1 in the top emerging in-demand skill in Malaysia, and this growing trend has just get started – the reason being the shortage of data professionals in the country is still at an all-time high.

Hence, just scroll through the relevant job portals or platforms, you’ll find that many data-related roles are still vacant due to the local tech talent gap.

As at April 2021, there were more than 240,000 digital talents in Malaysia that had LinkedIn profiles; more than half of them were located in Selangor or Kuala Lumpur.

Data science skills are applicable across different sector and industry, in fact as we move into the Industry 4.0 and Big Data era, it is inevitable for companies to evolve and harness the data that they are currently generating or have acquired in the past. So, whether you’re in the finance, logistics, property sector, etc. learning data science skills will certainly accelerate your career growth.

What if you’re at your mid-career stage, should you learn data science?

If you’re currently a non/partial-technical professional or thinking to switch career into data science, there isn’t a greater time than this. This is because, through the accumulated years of experiences that you have, it’s probably the best moment as you already have acquired the domain expertise in your niche or market in which will tremendously help in your data science practice – having this means you know precisely which business questions or issue to solve using data science techniques and methodologies.

On the flip side, if you’re at an entry-level or early career stage, you might want to explore and determine what will your end-goal or ultimate purpose of learning data science is and the career path you’re embarking on.

You do not only need to have the technical skills like programming, statistics and mathematics knowledge but the ability to derive business insights from collected data – by truly understanding how a business operates in different markets and visualize it to tell a story from the data you’ve cleansed.

Data science is a life-long learning journey, especially as new and emerging technologies evolve, your career prospect will become extremely valuable and lucrative as you venture into different fields with your new-found knowledge and skill.

In short, whether you’re just starting out in your career, trying to switch into data science or becoming a data professional, learn the basics – the skillsets and industry knowledge to succeed that you can apply at work. Not to forget the open-source tools that are available which is part of a data scientist toolbox!

We hope this article has helped you gain a better understanding of the career prospect of becoming a data scientist. If you think data science is what you are passionate about, you can read more about how to break into data science with no technical background or join our Data Science 360 course to kickstart your journey in data science.

What other data science questions would you like us to answer? Let us know in the comments section below. Like us on Facebook and subscribe to our Youtube channel for more content like this.

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  1. PL Lee

    Your article should be dated. Information for the field is time sensitive. If the information give here is 3 years old. It may not be valid anymore.

    • Reuben Chng

      Good point. Check out the date above. 🙂

  2. Saw Leng

    Hi, may I know which country and universities are famous for this course?

    • Dr. Lau

      It depends on the focus of the data science degree you are looking for. Some data science programs focus more on the comp science part, and some focus more on the analytics and maths part. I find that most of the good programs are offered in UK and US, for example, MIT, CMU and LSE offered Master programs with a good balance in technical and theory.

  3. Mei

    I’m from a healthcare background. Did not really find something to specialise in so my job is mostly quality and operations. Would it be wise for me to go into this field to be employed? Also am I considered a fresh grad and getting a fresh grad salary despite my past experience?

    • Dr. Lau

      Hi Mei, certainly. Data Science is about using code to build mathematics and statistical models in a scalable fashion, and apply it to industry problems. In fact, domain knowledge is the key and your unfair advantage, especially healthcare is such a hot field right now.

      Another misconception is the fresh grad part. No, you should never consider yourself a fresh grad. Your past experience is useful, you are an experienced team member with new skills, how do you think that sounds?

  4. Baoee

    How do I choose between math based and comp sc based data science degree?

    • Dr. Lau

      Hi Baoee,

      Maths based data science degrees focus more on the fundamentals, statistical modelling, calculus, and etc. Whereas comp science based ds degrees focus more on the algorithms, and other computer subjects e.g. networking, operating systems, and computer architectures. Which one are you interested in?

  5. Lee

    Any idea on how is the masters of data science and analytics offered by USM and masters of data science offered by UM? Thanks in advance.

    • Dr. Lau

      What I like about both degrees are:
      – Programming for data science
      – Machine Learning for Data Science

      What I like about USM:
      – Multimodal IR
      – Data visualization and visual analytics
      – Text and speech analytics

      What I like about UM
      – Research methodology
      – Data mining

      Both universities are teaching Big Data, which is good to have but not so applicable in the industry and research field. On the technical side, Hadoop is a good technology, but the adoption rate in Malaysia is super low. Which means you have a slim chance of getting a job afterwards.

      Both universities also do not cover much on data engineering and even the foundation of data science. it is due to the design of the course and they can’t cover that many topics.

      Most data science graduates focus too much on the data analytics part and neglect other important aspects. You should look into these areas for example unstructured data, text mining (includes topic detection, sentiment analysis), and multimodal IR (how to combine text, audio and video)

      Other factors you might want to consider while selecting between these two universities are their industry connection and facilities. Most data science services are cloud-based today, except for deep learning that requires GPU. A university that provides better facility will also be a plus point.

      • Fadhil

        Hi Dr Lau,

        That’s a good insight. As costs is my biggest constraint, I can only choose local uni to do Masters in Data Science. Which university would you recommend?

        • Dr. Lau

          For local universities, I quite like UM and UTM for their course structure, alumni network, and also their facilities. Maybe you can share with me what is your career goal such as the role and industry you want to be in, and also some of your current findings for local data science programs? Then I can point you in the right direction.

  6. Nicholas Tee

    Hi Dr.Lau,

    What do you think about studying abroad for Data Science related course, such as studying in Singapore? Is the degree more valuable as compared to studying locally in Malaysia? Would be grateful if you could provide the pros and cons for both overseas and local studies.

    Thank you in advance.

    • Dr. Lau

      As long as you can afford, it would be best if you studied abroad. When you study oversea, you get to mix with the locals, learn how they work, experience their culture. I studied Diploma in Singapore for 3 years and worked for 3 years before I further study in Australia, it was a great experience.

      We can evaluate the degree base on course structure and the university QS ranking. The course structure is somewhat similar. Let’s compare Data Science And Analytics by (NUS) vs Bachelor of Computer Science (data science) by UM. Both cover the introduction to data science, mathematics, statistics, data structure, database design. Both also offer electives on business, networking, and some advanced topics.

      Both NUS and UM are recognised globally so you won’t have a problem further study in Master or PhD. Ranking wise NUS is higher and is in the top 1% of world universities. But data scientist is still highly in-demand, and employers assess your skills first.

      There aren’t any obvious cons studying in Singapore. Their school fee is reasonable and international students can apply for a tuition grant. Some might say the living cost is expensive because of the currency, but you can make it up with part-time jobs.

      The only downside studying in Singapore is that their people, culture, environment are like Malaysia. You might want to explore studying in Australia? I can provide some information if you need further details.

  7. Ray

    Hi Dr Lau,

    Which private universities do you recommend for Data Science degree programme?

    a) Monash University – Bachelor of Computer Science in Data Science
    b) Heriot-Watt University – Bachelor of Science (Hons) in Statistical Data Science
    c) Asia Pacific University (APU) – Bachelor of Science (Hons) in Computer Science with a specialism in Data Analytics
    d) Taylor’s University – Bachelor of Computer Science (Hons) with a specialism in Data Science

  8. Chloe Ang

    Hi Dr Lau ,May I ask if you recommend to study statistical data science in the university of Heriotwatt Malaysia?

    • Dr. Lau

      Hi Chloe,

      It depends on your career path. This degree suits someone who wants to become a data analyst. In particular areas like finance, banking, and insurance. Because many of the subjects focus on financial mathematics and actuarial science.

      If you take a closer look at their electives are also related to finance. E.g. finance reporting, portfolio theories, and derivative markets. For the same reason, this course will lay a foundation if you plan to work as a researcher, quant, or pursue a Masters or PhD. degree.

      This degree doesn’t cover typical subjects such as Python programming, data structure, algorithms, database designs, and SQL. You might want to consider other degree programs if you are looking for a more technical career path: E.g. data scientist, big data analyst, machine learning engineer, or AI developer.

  9. Leyla

    Thanks for the beneficial insight. What do you think of the course Bachelor Hons in Data Analytics at Asia Pacific University, Malaysia? Does the syllabus cover the important aspects needed for this career?

  10. Ching

    Hi, for USM elective courses: among business analytics elective and multimodal analytics elective, which one do you recommend?

    Business analytics consists of Consumers Behavioural & Social Media Analytics, Business Intelligence & Decision Analytics, Predictive Business Analytics.

    Multimodal analytics consists of Multimodal Information Retrieval, Text & Speech Analytics and Forensic Analytics & Digital Investigations.

    Thanks in advance.

    • Dr. Lau

      Hi Ching,

      It depends on your career goal. Business analytics is generally more applicable. Most data analyst jobs require BI and predictive analytics. Consumers behavioural and social media analytics are handy in most customer-oriented industries. E.g. retail and e-commerce.

      I chose multimodal analytics during my uni time because I am interested in forensic. Also I like to learn how to analyze structured data since I was already pretty well-versed in software development at that time.

  11. Christina

    Hi Dr. Lau

    I would like to ask which university in Malaysia do you recommend for Master data science programme?

    Personally, I wish to learn more on analytics and modeling.

    Thanks in advance.

    • Dr. Lau

      Hi Christina,

      Have you shortlisted any universities? Let me know the top 3 in your mind and I will be able to guide you. It is rather hard to prescribe a single on given that they all have its own pros and cons. You may also refer to this video for some guidance.

      • Chai Keng Fui

        Hi Dr.Lau, is there a doctoral program in UTAR Kampar for data science? If yes, what is the entry requirement? Is it enough to have degree in mathematics science (Statistics) with a MBA?

  12. Puteri

    Hai, considering Data Science for my degree this year. Not sure what is written for me in the future. Maybe answering some questions in my head will help me put myself to ease

    So, some of my questions are
    -Where can I apply for careers with a Data science degree
    -Is it appropriate to study for masters and PhD right after degree in Data Science, will that help me in securing a career?
    -Is Data science in high demand in 3-5 years from now?

    • Dr. Lau

      1. Most companies are looking to hire data science professionals, from data engineers, data analysts, to data scientists. They advertise on their company career page or job portals.
      2. A master or PhD is not required to secure a data science job unless you want to venture into academic research.
      3. Do you think we will have more data in the next 3-5 years from now? That is your answer 🙂

  13. Oscar

    Hi Dr Lau, TARUC is offering Computer Science Degree In Data Science since 2019. Do you recommend me to enrol to the course and what are the thoughts from you? Below are their programme outline
    Introduction to Computer Systems
    Web Design and Development
    Software Engineering
    Internet of Things
    Introduction to Computer Networks
    Data Science
    Statistics for Data Science
    Artificial Intelligence
    Machine Learning
    Data Engineering
    Business Intelligence
    Data Warehouse Technology
    Cloud Computing
    Problem Solving and Programming
    Database Management
    Advanced Database Management
    Object-Oriented Programming
    Research Methods
    Data Structures and Algorithms
    Social and Professional Issues
    Probability and Statistics
    Discrete Mathematics
    Project I
    Project II
    Industrial Training (6 months)
    Electives (Choose 3):
    Introduction to Computer Security
    Mobile Application Development
    Natural Language Processing
    Graphics Programming
    Image Processing
    Algebra and Calculus
    Music Appreciation
    Introduction to Short Story
    Free Module Electives (Choose 1):
    Business Organization and Management
    Principle of Marketing

    • Dr. Lau

      Hi Oscar,

      Have you watched this video ?

      If you have, I got two questions for you:
      – What is your career goal / plans?
      – If you have not decided, at least tell me what are your interest area, that will help to provide relevant input for your questions.


      • Oscar

        Hi Dr Lau,

        I have definitely watched your video. Data Scientist will be my first career option, follow by Data Analysts. FYI, I am finding tertiary education for Data Science. I am just getting trouble what university that suit me. For now, APU and TARUC are under my consideration. I would like to ask you which university will you recommend me more. Thanks for your comment!

        Btw, this was the syllabus that TARUC lecturer gave me

        Basic and inferential Statistics
        Mathematical concepts (linear algebra and multivariate calculus)
        Classical Machine Learning (supervised and unsupervised)
        Artificial Intelligence (Deep Learning that involves neural networks)
        Visualization and Reporting (using Tableau, QlikView, etc.)
        Big Data Storage (using Hadoop, Hive, etc.)
        Databases (Relational: SQL, MongoDB, Non-Relational: NoSQL, etc.)
        Machine Learning on Cloud (AWS, Azure, etc.)
        Analytical tools (R, Python, Apache Spark, SAS, etc.)
        Real-Time Data Handling (Apache Kafka, Amazon Kinesis, Flink, etc.)
        Data Science Project Management Method (CRISP-DM)

  14. Tasnim

    Hi Dr. Lau,

    I’m considering pursuing my postgraduate study in Data Science. I have done some research and highlighted these two universities under my consideration. Those are:

    1. UM- Master of Data Science (Coursework)
    2. Asia Pacific University- MSc in Data Science and Business Analytics

    Which one do you think is better in terms of the course structure that I can benefit the most once I graduated? As for my career-path concern, I’d like to navigate my path into data science.

    A little bit on my background:
    Recent graduate in Bachelor of Economics (Honours) – 2021
    Equipped predictive analysis for Business and Economics Forecasting – R programming

    Could you advise me on this matter? Thank you so much.

  15. Denise

    Hii , I’m thinking of studying a degree computer science in data science in Monash university malaysia.

    Do you think it’s good to study there in terms of the course ?
    Once I graduate will it be easy to look for a job in Malaysia ?

    • Dr. Lau

      Hi Denise,

      You may refer to this guide on how to choose a university for your data science degree. In general Monash is ok, but you need to check if their curriculum matches your career goals. If you graduate on time, there should still be increasing number of job opportunities from now till 2025.

  16. Chai Keng Fui

    Hi Dr.Lau, is there a doctoral program in UTAR Kampar for data science? If yes, what is the entry requirement? Is it enough to have degree in mathematics science (Statistics) with a MBA?

    • Dr. Lau

      Hi Keng Fui,

      Yes there is. Your bachelor and Master’s degree should be sufficient (subject to your CGPA). You may look into their PhD in Science or Computer Science. Also try to search for the lecturers who are accepting PhD students and look at their research directions. That will help you in the process when you are proposing your research and thesis title.

  17. Michael

    Hi Dr. Lau, I’m currently considering taking Data Science as a second or possibly switch-to Major at WMU (Michigan) but looking at the course structure, it is a 45 credit hour major. I’m a little skeptical about the content of their syllabus (listed below). I would like to become a Data Scientist working with researchers in the medical or astrophysics field mostly. Do you have any advice?

    Elementary Linear Algebra
    R Programming for Data Science
    Storage, Retrieval, and Processing of Big Data
    Machine Learning
    Software Systems Development I: Requirements & Design
    Satisfies Baccalaureate Level Writing Requirement
    Software Systems Development II: Implementation, Testing
    Data Analysis Using R
    Introduction to Mathematical Statistics Using R
    Introduction to Statistical Computing
    Regression Analysis
    Big Data Analysis Using Python

    Applied Data Mining
    Appl Multivariate Stat Method
    Nonparametric Stat Methods
    Time Series Analysis
    Stat Design/Analysis Exper
    Computer Based Data Analysis
    Graphical User Interface Dev
    Intro to Web Technologies
    Computer Security & Info Assurance
    Computer Networks
    Design of User Interfaces
    Artificial Neural Sys
    Parallel Computations
    Comp Modelling/Simulation
    Database Systems
    Database Mgmt Systems

  18. Sam

    Hi, I was wondering what was the base salary a foreigner from EU with a master’s degree in NLP could ask when applying for a Data Scientist position in Malaysia ? Do you think the market in KL has opened more to foreigners ? Is it easy to get sponsored for a work visa as a fresh graduate ? Thank you.

    • Dr. Lau

      Hi Sam, it’s not so much about your degree, it’s more about the company. What are the problems they are solving, what type of talent they are looking for, etc? Typically data scientists in KL gets paid around RM 5,000 – RM 7,000. More companies are looking to hire and expand after 1st May, and KL definitely has more opportunities compared to other states. May I know what is your bachelor degree and do you have any work experience prior to this?



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