Job Demand & Salary for Data Scientists in Malaysia According to MDEC

Excellent Job Prospects for Data Science or Data Analytics Graduates in Malaysia

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Statistics show that by the year 2020, there will be about two million job openings for data professionals and that the demand for people with this knowledge and skill will outstrip supply by a ratio of two to one. It’s a global phenomena which is already in motion and Malaysia has set its sights on developing 20,000 data professionals and 2,000 data scientists by 2020.

There are three main streams data professionals can branch out into – data scientists, data analysts and data engineers. While a career in data engineering would revolve around a job that is quite technical (imagine a mechanic working on a car), he or she is said to look at data a little differently compared to a data analyst, who is trained in programming skills, with a little aptitude in statistics and comes from a mathematical background.

Data scientists also are put on a higher pedestal, as this person is required to deal with higher levels of big data technicality and complexity. Soft skills are also very important and is also key in this profession because you need to translate complex situations into simple business language. A data professional must be able to take all the information, develop a mathematical formula, come up with a conclusion and present it to the top management – that is the skill required.

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Data Science Job Demand in Malaysia

EduSpiral picked me up from KL Sentral to tour the campus & provided counseling to help me make the right choice.

EduSpiral picked me up from KL Sentral to tour the campus & provided counseling to help me make the right choice.
Qi Leem, Software Engineering Graduate from Asia Pacific University (APU)

Data-centric industries including business services, information technology, banking and Telecommunications are leading the way with data science recruitment in Malaysia. Common business applications with predictive analytics include personalised marketing, managing the customer lifetime value, identifying risk and forecasting supply. Deep learn-ing and natural language understanding technologies are topical; while communications, geospatial and biomedical data are of high interest.

Job-seekers for data science roles require baseline higher education, holding a Bachelor’s Degree at a minimum. Employers however value short courses and MOOCs in resumes as they reflect active lifelong learning and commitment.

While a PhD is not a prerequisite to becoming a data scientist, advanced education is valued. Soft skills such as critical and creative thinking are sought after. Finding an individual that is strong in all the competencies for a data scientist is very rare: the formation of teams with complementary skill sets can address this challenge. Ultimately, employers desire team members who will add value to the ‘bottom line’ of a business through delivering actionable insights.

Employers indicated expansion of hiring for data science teams, although recruitment is still at an early stage in Malaysia. The size of data science teams, requirements and salary expectations varies with the maturity and size of organization and industry.

Many employers are building their teams from ‘scratch’, accepting candidates with entry-level industry experience. The large salary range reported by employers for a data scientist from more than RM 15,000 per month to less than RM 5,000 per month may reflect a lack of precision in defining the role of a data scientist. While compensation will differ by candidate experience and performance, it is important that this role is not undervalued. Data science competencies such as statistical modelling and machine learning require a high education investment which should be recognised.

Job Description for a Data Scientist in Malaysia

Software Engineering at Asia Pacific University (APU)

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Zen Yi, Graduated from Software Engineering at Asia Pacific University (APU)

The 3 key roles identified for data science teams represent natural areas of focus and division of labour:

  • Data Scientist – Use analytical techniques combined with data skills to develop scalable and robust analytical models
  • Data Engineer – Design and develop high-performance infrastructure and tools to enable users to consume and understand data more effectively
  • Data Analyst – Communicate insights that deliver business value based on exploratory analysis

The most common job titles used by our reviewers were data analyst, data scientist and data engineer. The amount of demand for data analysts in the job market should not be under-estimated. Data analysts may play an important role in deriving value from data assets while companies build out their predictive capabilities.

While some employers are still recruiting for data modellers and data miners, we anticipate that these titles will be eventually encompassed and replaced by ‘data scientist’; skills such as programming and data wrangling are likely to be enhanced by these professionals.

Other titles that employers used included data architect, data visualization engineer, soft-ware research engineer, research analyst, researcher, statistician and actuary. A data science team may also be supported by other roles such as chief data analytics officer, database administrator and data governance officer. It should be noted that several job titles may refer to a similar role. For example, a data engineer may be called a software engineer or big data engineer.

What Qualifications do Employers Prefer for Data Scientists in Malaysia?

A Bachelor Degree was a minimum requirement by most employers for the job roles in Data Scientist, Data Engineer and Data Analyst. Notably, some employers also required short course training and MOOCs, highlighting the importance and value of extra-curricular learning activities.

While a PhD was not regarded as mandatory for a Data scientist role, some employers wanted at least a Master’s degree, indicating the advanced knowledge desired.

Is Industry Experience Needed to Become a Data Scientist in Malaysia

Many employers were willing to recruit data scientists with entry-level industry experience. These employers are building their teams from the ground up, a reflection that the data science recruitment landscape in Malaysia is still at an early stage. Strong education backgrounds of candidates would be vital for building these types of teams.

Salary Expectations for Data Scientists in Malaysia

While the highest bracket a data scientist could expect was more than RM15,000 per month, the highest bracket for data engineers and data analysts was RM8,001 – RM15,000. The skills that differentiate data scientists, namely, statistics and modelling and machine learning competencies, can add high value to a graduate’s earning potential.

Some employers offered less than RM5,000 per month for a data scientist. The large range in salaries could be due to the maturity and size of organizations. Employers are also likely to be compensating based on experience and past performance of candidates. However, some organizations could be using ‘data scientist’ as a catch-all job title for roles with lower skill requirements, thereby undervaluing the role.

Capacity

Most employers reported increased capacity for data science teams for 2017 – 2020. While many employers indicated the current and future capacity for each type of role was less than 5 people, some organizations said they were willing to recruit up to 30 data scientists between 2017 – 2020. Employers should be careful to distinguish the functionality between data science roles to ensure successful recruitment.

CORE FUNCTION AREAS

The functions of a data science team can be divided into 7 core areas:

  1. 1. Business analysis, approach and management
    Problem framing, experimentation and benefits realization
  2. Insights, storytelling and data visualization
    Communication of insights that can guide actionable results
  3. Programming
    Data sourcing, integration, scaling and optimization
  4. Data wrangling and database concepts. Ensure provenance and hygiene of data for trusted insights
  5. Statistics and data modelling. Identifying factors and relationships to make predictions for competitive advantage
  6. Machine learning algorithms. Classification and prediction for intuitive results at scale
  7. Big data. Remove constraints on volume, variety and velocity of data

Best Education Pathway to Become a Data Scientist in Malaysia

Students after SPM or O-Levels may go for the Foundation in Arts, Foundation in Science or Foundation in Computing for 1 year before continuing on to the 3-year Data Science or Data Analytics degree at a top private university in Malaysia.

On the other hand, with 3 credits in SPM or O-Levels including Maths, students may go for the 2-year Diploma in Information Technology and then enter into Year 2 of the Data Science or Data Analytics degree.

Pre-University students with the relevant results in STPM, A-Levels, SAM, AUSMAT, etc. can enter directly into Year 1 of the Data Science or Data Analytics degree as long as they meet the minimum entry requirements. Please take a picture of your results and WhatsApp to 01111408838 for evaluation for entry into top universities in Malaysia for Data Science.

Study Data Science at Top Private Universities in Malaysia

EduSpiral took me & my friends to tour a few universities to help us make the right choice. He then met me & my father for further counseling & to assist in registering. Horng Yarng, Diploma in ICT at Asia Pacific University (APU)

EduSpiral took me & my friends to tour a few universities to help us make the right choice. He then met me & my father for further counseling & to assist in registering.
Horng Yarng, Diploma in ICT at Asia Pacific University (APU)

Data science, also known as data analytics or data-driven science, is an interdisciplinary field about scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.

Data science is a multidisciplinary blend of data inference, algorithm development, and technology in order to solve analytically complex problems. At the core is data. Millions of raw information, streaming in and stored in enterprise data warehouses. Much to learn by mining it. Advanced capabilities we can build with it. Data science is ultimately about using this data in creative ways to generate business value

Data scientists combine statistics, mathematics, programming, problem-solving, capturing data in ingenious ways, the ability to look at things differently to find patterns, along with the activities of cleansing, preparing, and aligning the data.

Dealing with unstructured and structured data, Data Science is a field that encompasses anything

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related to data cleansing, preparation, and analysis. Put simply, Data Science is an umbrella term for techniques used when trying to extract insights and information from data.

A degree in Data Science or Data Analytics will cover the following areas of study:

  • The ability to develop technical knowledge, skills and background in the design and organisation of computer systems with an emphasis on data analytics.
  • The ability to critically evaluate design paradigms, languages, algorithms, and techniques used to develop complex software systems.
  • The ability to evaluate and respond to opportunities for developing and exploiting new technologies with data analytics concepts and tools.

Three of the top award-winning private universities offering the Data Science degree courses are

  1. Heriot-Watt University Malaysia offers the BSc in Statistical Data Science
  2. Asia Pacific University (APU) offers the BSc (Hons) in Computer Science with specialism in Data Analytics
  3. Multimedia University (MMU) offers the Bachelor of Computer Science (Hons.) Specialising in Data Science.