Best Education Pathway to Become a Data Scientist in Malaysia is Getting a Degree from a Top University

How to Become a Data Scientist in Malaysia?

Because there is simply too much information for the average person to process and use, data scientists are trained to gather, organize, and analyze data, helping organisations make sense and strategies from the vast amounts of data.

Now that you have decided to study data science in Malaysia, you will need to figure out which university can equip you with the necessary knowledge and skills to be successful in this career. First of all, your results must meet the entry requirements to join the Foundation or Pre-University course. Upon completion of the Pre-U, you will then enter the Data Science degree for 3 years.

Studying at the top ranking university in Malaysia gives you a lot of opportunities in your future professional life. Top universities provide a high standard of education that equips you well for your future career.

Data scientists come from a wide range of educational backgrounds, but recently private universities in Malaysia have started to offer degree programmes in Data Science. Additionally, Data science degrees include a wide range of computer-related majors, but it could also include areas of math and statistics. A Data Science degree from a top private university in Malaysia would equip you with all the necessary knowledge and skills to become a successful professional in this field.

Furthermore, a degree earned at a reputable university in Malaysia makes seeking employment much easier whether locally or globally. Part of finding the right university in Malaysia for you will be picking out the criteria that matters to most to you, and then seeing if any of the top private colleges or universities in Malaysia that you’re looking at fit those criteria. University Rankings, Awards & Achievements are indicators of the level of standard that they have achieved and these could serve as a guide for you in choosing the right university to study at.

Choosing the right university to study Data Science can be a complicated and confusing process. There are many universities offering this course but not all Data Science courses are the same at each university. It is important to understand the differences to see which one fits your future career goals.

There are many factors involved in making this choice therefore contact me for a free consultation. I have more than 20 years experience in the education industry and is knowledgeable of the ins and outs of the private universities in Malaysia to be able to assist you in making this important decision.

The Best Education Pathway to Become a Data Scientist in Malaysia through an Undergraduate Programme at a Top Private University

Basically, a data scientist is someone who gathers and analyzes with the goal of reaching a conclusion. They do this through many different techniques. They may present the data in a visual context, which is often called “visualizing the data,” allowing a user to look for clear patterns that wouldn’t be noticeable if the information was presented in hard numbers on a spreadsheet.

They often create highly advanced algorithms that are used to determine patterns and take the data from a jumble of numbers and stats to something that can be useful for a business or organization. At its core, data science is the practice of looking for meaning in mass amounts of data.

Data science, which is a newer field, is heavily based on the use of computers and technology. It accesses information from large databases, uses code to manipulate data, and visualizes numbers in a digital format.

There are many pathways to getting a career in data science in Malaysia, but for all intents and purposes, it is completely impossible to launch a career in data science without a university education. You will need at least a 3-year bachelor’s degree.

Who Should Study Data Science in Malaysia?

So what are the top traits of a data scientist? How can you determine if you have the raw material needed for a long career in the field of data science? There are many unique characteristics that apply to data science, so it’s likely you have one or more of these skills.

First of all, you must have a curious nature that pushes a constant pursuit of learning. There are so many areas and so many data points to analyse, that a data scientist must have an inborn curiosity that drives your need to find answers from the data.

You’ll also need a strong ability for organisation. As there are millions of potential data points, so keeping each piece of information organised in a useful way is important. Good organisation will help you reach the right conclusions at the end of your work. You may find the work frustrating at times where you must keep on reorganising and reanalysing until you find the right answer.

Other traits, like creativity, the strong ability to stay focused, and an acute attention to detail, will all help you in becoming a data scientist.

Steps to Become a Data Scientist in Malaysia

Step 1 – Complete a Pre-University Programme

Students after SPM or O-Levels will need to go for a Pre-University programme such as Foundation, SACE, AUSMAT, CIMP, A-Levels, STPM, etc before entering a degree programme in Data Science. You will need at least 5 credits in SPM or O-Levels including Maths.

If you’re sure of pursuing a career in Data Science, you can just take the Foundation in Computing & Technology at a top private university. It would be easier and cheaper than the external Pre-University programmes.

Step 2 – Earn a bachelor’s degree in Data Science from a Top Private University in Malaysia

Some private universities in Malaysia offer data science degrees, which is an obvious choice. This degree will give you the necessary skills to process and analyse a complex set of data, and will involve lots of technical information related to statistics, computers, analysis techniques, and more. Most data science programs will also have a creative and analytical element, allowing you to make judgment decisions based on your findings.

During your undergraduate studies you will become proficient with the most widely used programming languages in data science such as Python, Java, and R — and refreshing their knowledge in applied math and statistics. In addition, continue to learn programming languages, database architecture, and add SQL/MySQL to the “data science to-do list.”

The most sought-after majors for data science are statistics, computer science, information technologies, mathematics, or data science (if available). Now is the time to start building professional networks by looking for connections within your university, look for internship opportunities, as well as, ask lecturers and advisors for guidance.

During your university studies, it is also important to improve your command of the English language, communication skills, critical thinking skills, and leadership skills. Not all Data Science degree programmes are the same. It is important for students to look at the subjects offered to see if they fit your career goals.

Step 3 – Apply for a Entry Level Position in Data Science

There is a tremendous requirement for Data Scientists and Big Data Specialists worldwide now and in the future, with hundreds of thousands of new job opportunities emerging globally. In Malaysia alone, by the year 2030 this need is expected to reach at least 20,000 data professionals and 2000 data scientists. Job demand as well as salary for qualified Data Scientists or Big Data Professionals in Malaysia is high.

Data science fresh graduates can demand starting pay in the range of RM4,000-RM8,000 — making it the highest paid entry level job in the country today. Furthermore, an experienced professional in the field can demand up to RM15,000 a month.

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.

Why Study Data Science at a Top Private University in Malaysia?

Studying at the top ranking university in Malaysia gives you a lot of opportunities in your future professional life. Top universities provide a high standard of education that equips you well for your future career.

Furthermore, a degree earned at a reputable university in Malaysia makes seeking employment much easier whether locally or globally. Part of finding the right university in Malaysia for you will be picking out the criteria that matters to most to you, and then seeing if any of the top private colleges or universities in Malaysia that you’re looking at fit those criteria. University Rankings, Awards & Achievements are indicators of the level of standard that they have achieved and these could serve as a guide for you in choosing the right university to study at.

Choosing the right university to study Data Science can be a complicated and confusing process. There are many universities offering this course but not all Data Science courses are the same at each university. It is important to understand the differences to see which one fits your future career goals.

How to Become a Data Scientist or Data Analyst in Malaysia?

What is a Data Scientist?

Data scientists must have expertise in several different disciplines. Generally, data scientists must possess the statistical knowledge and computer skills that are needed for solving complex problems. Using descriptive, predictive, inferential, and causal models, they can explore and anticipate problems then work to model a solution based on a multitude of factors.

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.

Data scientists are part mathematician and part computer scientist. Their skill set encompasses both the business and information technology sectors, which is why they are highly sought after.

Data science is deep knowledge discovery through data exploration and inference. This discipline focuses on using mathematical and algorithmic techniques to solve some of the most analytically complex business problems. In doing so, they leverage troves of raw data to figure out the hidden insight that lies beneath the surface. The core of the field centers around evidence-based analytical accuracy and building strong decision capabilities. However, data scientists must also verbally and visually communicate their findings to stakeholders who may or may not understand the statistical jargon. Thus, data scientists must be excellent communicators.

What is a Data Analyst?

A data analyst is someone who collects, processes and performs statistical analyses of data. They translate numbers and data into manageable ideas, concepts and strategies so that organizations and companies in Malaysia are able to make better business decisions.

Whether it be market research, sales figures, logistics, or transportation costs, every business collects data. A data analyst will take that data and figure out a variety of things, such as how to price new materials, how to reduce transportation costs, or how to deal with issues that cost the company financially.

Data analysts can determine how data can be used in order to answer questions and solve problems. They study what’s happening now to identify trends and make predictions about the future. They are like detectives, figuring out how things work and helping to make sense of the vast amounts of data.

Data analysts typically use computer systems and calculation applications to figure out their numbers. Data must be regulated, normalized, and calibrated so that it can be extracted, used alone, or put in with other numbers and still keep its integrity. Facts and numbers are the starting point, but what is most important is understanding what they mean and presenting the findings in an interesting way, using graphs, charts, tables, and graphics.

Data analysts may have the following responsibilities:

• Working with technology teams, management and/or data scientists to set goals
• Mining data from primary and secondary sources
• Cleaning and dissecting data to get rid of irrelevant information
• Analyzing and interpreting results using statistical tools and techniques
• Pinpointing trends and patterns in data sets
• Identifying new opportunities for process improvement
• Providing data reports for management
• Designing, creating and maintaining databases and data systems
• Fixing code problems and data-related issues

A data analyst’s skills may not be as advanced as a data scientist’s skills, but their goals are very similar. Data analysts are sometimes called “junior data scientists” and may be limited to handling specific business tasks using existing tools, systems and data sets.

What does a Data Scientist or Data Analyst do?

Essentially, a data scientist extracts meaning from the varying types of data (e.g., structured, unstructured, semi-structured) that flow into the enterprise. On any given day, a data scientist may be extracting data from a database, preparing the data for various analyses, building and testing a statistical model or creating reports that include easily understandable data visualizations. There is a data science cycle which isn’t a set of rules as much as it is a heuristic:

• Data collection
• Data preparation
• Exploratory data analysis (EDA)
• Evaluating and interpreting EDA results
• Model building
• Model testing
• Model deployment
• Model optimization

The above is iterative, meaning a data scientist will be in “evaluation mode” throughout the entire process. Or, perhaps, after the EDA phase, they find that the data doesn’t fit the problem they are trying to solve (or the question they are attempting to answer). They may need to start over or carefully choose which portions of the data that does apply, then go back and collect additional data. Such is the reason they need a higher level of combined skills including research design.

Job Description for a Data Scientist or Data Analyst in Malaysia

While data science projects and tasks may vary depending on the enterprise, there are primary job functions that tend to be common among all data science positions such as:

• Collecting massive amounts of data and converting it to an analysis-friendly
• Problem-solving business-related challenges while using data-driven techniques and tools.
• Using a variety of programming languages, as well as programs, for data collection and analysis.
• Having a wealth of knowledge with analytical techniques and tools.
• Communicating findings and offering advice through effective data visualizations and comprehensive reports.
• Identifying patterns and trends in data; providing a plan to implement improvements.
• Predictive analytics; anticipate future demands, events, etc.
• Contribute to data mining architectures, modeling standards, reporting and data analysis methodologies.
• Invent new algorithms to solve problems and build analytical tools.
• Recommend cost-effective changes to existing procedures and strategies.
• Data Scientist Skill Set
• Experience and Fluency in many of these computer/coding programs: SAS, SPSS, MATLAB R, Python, Java, C/C++, Hadoop Platform, SQL/NoSQL Databases.
• Business Savviness: Data scientists need to understand the business sector they are working in and create solutions to complex problems that align with business logic/objectives.
• Communication skills: A data scientist can clearly and fluently translate their technical and analytical findings to a non-technical department. They must also be able to understand the needs of their non-technical departments (such as business development or marketing teams) in order to analyze the data correctly. A data scientist must empower the business to make decisions by presenting robust and verifiable information.
• Expert Technical skills in the following:
  • Math (g., linear algebra, calculus, and probability)
  • Statistics
  • Machine learning tools and techniques
  • Data mining
  • Data cleaning and munging
  • Data visualization and reporting techniques
  • Unstructured data techniques