How To Become A Data Scientist In Singapore - 2023 (2023)

Table of contents

      • What is Data Science?
      • Data Scientist Demand in Singapore
      • Data Science Jobs and Salaries in Singapore
      • Industries that Hire Data Scientists in Singapore
      • Skills Required to Become a Data Scientist in Singapore
      • Wrapping Up

In the age of digital transformation, data has become an enormously powerful tool. As a result, Data Science has become the new buzzword.

Data Science gives useful insights through data and allows businesses to deliver more relevant products to their customers. This is one of the reasons why the demand for a data scientist is on a rise in every country that wants to lead in the field of technology.

Singapore, being one of the hottest centers of technological advancements, has seen rapid growth in the data science industry. This is one of the reasons why there is a rising demand for data scientists in Singapore.

In this article, we will discuss the basics required to be a data scientist, the reason for the high demand of people in this domain, and more. Here is a brief outline of the topics covered:

(Video) What Makes a Good Data Scientist in Singapore's Job Market?

  • Who is a data scientist?
  • Why is there a Data scientist demand in Singapore?
  • What are the different Data science jobs and salaries in Singapore?
  • Which Industries hire Data Scientists in Singapore?
  • What are the skills required to become a Data Scientist in Singapore?

What is Data Science?

In simple words, a data scientist is a combination of a computer scientist and a mathematician. Adept in analyzing data, data scientists utilize their analytical, statistical, and coding skills to collect, analyze, and interpret large data sets. This information is then used in developing data-driven solutions to solve business problems.

They are excellent trend spotters who can leverage the power of data to generate more meaningful insights. Data Scientists have strong problem-solving skills, experience with computer languages such as Python, SQL, and R; knowledge of statistics, machine learning techniques, data mining, and deep learning. Additionally, they also need to have good communication skills to interact with decision-makers and managers of the company.

Free eBook: Data Science and Business Analytics Career Guide

Data Scientist Demand in Singapore

There has never been a shred of doubt about Singapore’s growth potential in the field of technology, given its steady progress in the domain for the last two decades. This is one of the reasons why the top emerging jobs in Singapore are dominated by technology, and data science is one of them. Furthermore, this growth can be credited to the government of Singapore, which invests in digitalization and serves as a hub for tech giants and emerging startups to undergo a digital transformation.

A LinkedIn report stated that data science jobs worldwide had jumped by 17 times between 2013 to 2017 [1]. Furthermore, according to LinkedIn’s “2020 Emerging Jobs Report Singapore, the role of a data scientist is amongst the top 5 positions in the country [2]. Looking at this, it is highly likely that the demand for data scientist jobs in Singapore will only trend upwards in the future.

Singapore’s Economic Development Board (EDB) has stated in its report that the data analytics industry contributes an estimated USD 730 million to the economy annually [2]. The Nanyang Technological University (NTU) has launched a Data Science and Artificial Intelligence Centre in 2017 [3], which has received a funding of USD 5.85 million in the last three years[2].

These initiatives show that the government and educational institutions’ efforts, coupled with the interest of the public in learning about this domain, data science has carved a distinct niche for itself in Singapore.


There are many data science jobs available in Singapore due to the growing demand in the industry and also the presence of data in ever larger quantities. In 2018, Facebook announced the expansion of its data center network to Asia by investing USD 1 billion [4], which generated more curiosity amongst professionals who wanted to get into this field or were already a part of the data science domain.

Read More: How Data Science will Emerge as a Career post COVID-19

Data Science Jobs and Salaries in Singapore

There are various roles associated with the domain of data science and analytics. So if you are interested in becoming a data scientist, you may explore other related roles as well, including:

  • Data Scientist
  • Data Engineer
  • Machine Learning Engineer
  • Data Analyst
  • Business Analyst
  • Statistician

When it comes to job opportunities, a large chunk of the openings are seen in the IT sector and banks, who also continue to be the highest payers. Since it is a niche field, companies prefer experienced professionals who have substantial work experience in handling real-time projects. Professionals who work in this domain work with sensitive data. This is one of the primary reasons why data science job openings are for permanent roles and we don’t often see internships or temporary work arrangements.

The median salary is under S$5,000 a month for junior or entry-level positions. About a third of the average salaries being offered by companies fall between S$3.50 and S$7,500. The median salary for senior data science professionals is above S$8,000[5].

Read More: Top 9 Job Roles in the World of Data Science for 2022

Industries that Hire Data Scientists in Singapore

Top industries that hire data scientists include the IT sector, Internet, Banking, Higher Education, Financial Services, to name a few. Global and Asian firms have come together to invest in their data hubs in Singapore to capitalise on the city’s ease of business and internet connectivity.

(Video) Is Data Science Dying in 2022?

As companies in Singapore get an overwhelming amount of data, they are constantly looking for data scientists who can establish a correlation between raw data points to generate actionable insights in today’s highly dynamic business environments.

Following are some of the popular data science companies in Singapore:

  • DBS Bank: A renowned MNC in the banking and financial domain with its headquarters in Singapore, it has a spectrum of products and services for which data and analytics are utilised extensively.
  • Google: The tech-giant offers numerous positions in its Singapore office for data scientists. With their core competency in the field of technology, they select applicants who have a minimum of 4-5 years of experience in this field.
  • EY: Information management, advanced analytics and business intelligence play a crucial role in this Big-4 company. To solve their requirements, the data and analytics team is always on a lookout for great talent.
  • IBM: IBM has a good reputation for working on real-world data science problems in a large array of industries, both internally and with IBM clients. They look for experienced candidates in Python, Statistics, Machine Learning, and building algorithms.
  • Twitter: No points for guessing that twitter is one of the most data-flooded social media platforms. It uses analytics and data science in multiple ways to assess user behaviour and use it to make their services better.

In addition to these well-established companies, there are a lot of startups in the data science domain, including Crayon Data, Tookitaki, Trax, and Tuple Technologies, to name a few. The amalgamation of a global talent pool, superlative infrastructure, and tech-savvy residents promises an exciting future for professionals in Singapore who aim at making a career in the field of data science.

Read More: Top 9 Data Science Books for Beginners

Skills Required to Become a Data Scientist in Singapore

When it comes to the skills required to become a data scientist, it is mainly divided into 2 parts:

1. Technical Skills
2. Non-technical Skills

Let’s talk about both in greater detail:

(Video) Why You SHOULDN'T Become A Data Analyst

1. Technical Skills for a Data Scientist

  • Knowledge of Statistics – As mentioned in the beginning of the article, a data scientist is both a programmer and a mathematician. Basic concepts of statistics such as descriptive statistics and probability theory will help you in making better business decisions from the data you retrieve from the database.
  • SQL – As a data scientist, you need to not only know how to apply algorithms but also fetch the data to be used for analyses. Thus, being an expert in SQL (Structured Query Language) will be very useful. SQL is specifically designed to help you access data from the database where it is stored, and communicate with it. It also helps in performing analytical functions and gives valuable insights when a query is applied to a database.
  • Python or R CodingPython is an easy to learn, robust, and versatile coding language. It has the most powerful libraries for math, AI, machine learning, and statistics. R programming also allows advanced statistical computing which is a big plus in data science. It provides an intensive environment for you to analyze, process, and visualize information.
  • Knowledge of SAS and Other Analytical Tools – Understanding of analytical tools will help you in extracting valuable insights from data sets. Multiple analytical tools are used by data scientists. Some of the popular ones are the Statistical Analysis System (SAS), Apache Spark, KNIME, QlikView, Splunk, Apache Hadoop, etc.
  • Handling Unstructured Data – Unstructured data refers to the undefined data that does not fit into a traditional row-column database. Examples of unstructured data include blog posts, social media posts, videos, audio files, etc. Since a business collects a large amount of unstructured data from different channels, as a data scientist you must be adept at understanding and managing it.
  • Data Visualization – A data scientist conducts a lot of analyses that may not make sense to a layperson. To communicate your insights to business stakeholders in an easy-to-comprehend manner (e.g, in the form of charts and graphs), you must have the ability to visualize data with the help of tools such as Tableau, ggplot, Matplotlib, etc.
  • Machine Learning – Knowledge of machine learning will take you one step ahead of your competitors in the field of data science. In-depth knowledge of techniques such as supervised machine learning, unsupervised machine learning, reinforcement learning, decision trees, and neural network, etc. will aid you in performing better at the job.

Read More: How to Get Into Data Science From a Non-Technical Background?

2. Non-technical Skills for a Data Scientist

  • Communication Skills – Since the job role of a data scientist requires you to communicate with people from both technical and non-technical backgrounds, you must have strong communication skills to put your points across to the target teams.
  • Business Acumen – To be a successful data scientist, you need to have a solid understanding of the functioning of your industry. Only once you can identify the problems that are crucial for your business will you be able to work on it to create valuable insights.
  • Domain Knowledge – Professionals from different fields are getting into data science. Whether you come from the hospitality industry, IT, telecom, or educational services, you need to have in-depth knowledge of your industry. It will enable you to derive meaningful insights in the context of your business, and thus aid in its transformation.
  • Teamwork – Last but not the least, teamwork is a very important part of being a data scientist. No data scientist works in isolation. You have to interact with people from different verticals to deliver the appropriate solution for the business problem. Thus, a healthy collaboration with different teams is a must for you.

Read More: Step-by-Step Guide to Becoming a Data Scientist

Wrapping Up

Now that you know about the growing opportunities in the field of data science in Singapore, you should work on improving your skills and aim for a better career. From healthcare and software to real estate and financial services, data scientists are required across all major industries. If you are aiming for a career transition or to get a high-paying job, start building up your skill-set steadily.

You can take the first step by enrolling in a data science course in Singapore. Great learning has collaborated with MIT IDSS and UT Austin to bring you the Applied Data Science Bootcamp (12 weeks) and the Post Graduate Program in Data Science and Business Analytics (6 months).

Both the programs follow a structured, mentored-learning approach blended with constant support and guidance. If you want to bag the next big data scientist job in Singapore, get your certification from one of the leading universities in the world for data science.

Liked the article? Let us know in the comments section about what you’d like to read next on our blog about data science.

Sources: [1] | [2] | [3] | [4] | [5]

(Video) Why you should not be a data scientist


How do I become a data scientist in Singapore? ›

Course / Programme Listing

Is data science still in demand in 2025? ›

The above projections are evident of the steep rise in the demand for Data Science professionals by 2025 and the boom in this profession will be observed in all the industries. No matter which niche you belong to, the demand for critical thinking and domain-specific skills will continue to increase in the near future.

Is Singapore good for data scientist? ›

Data scientists are now one of the top five in-demand employment roles in Singapore, according to the Robert Half Salary Guide. Companies are under increasing pressure to pay an attractive Data Scientist salary in Singapore to recruit in-demand talent as a result of these market conditions.

Is data science a good career in 2023? ›

Yes, data science is a very good career with tremendous opportunities for advancement in the future. Already, demand is high, salaries are competitive, and the perks are numerous – which is why Data Scientist has been called “the most promising career” by LinkedIn and the “best job in America” by Glassdoor.

Is 40 too old to become a data scientist? ›

So despite industry ageism, a recent study by Zippia showed that the average age of data analysts in the U.S. is 43 years old. This takes us back to our titular question: are you too old to start a new career in data analytics? The short answer, in our opinion, is no.

How much are data scientists paid in Singapore? ›

The average salary for Data Scientist is $6,000 per month in the Singapore.

Which country is best for data scientist? ›

The top countries that provide the best education in data science include the USA, UK, Canada, France, Australia, New Zealand. So far, the USA has been reigning the 1st position for masters in data science.

Which country pays best for data scientist? ›

Germany. Germany's strong economy allowed it to surpass Britain in terms of data science salaries. The average national wage in 2022 is $65,564 per year (additional compensation included). The lowest annual pay reported on Glassdoor is $49,633 and the highest is $80,031.

Is data science dead in 10 years? ›

So, until and unless we find a way to not use data itself, data science as a field is not going to be obsolete anytime soon. However, many believe that since a data scientist's daily tasks are quantitative or statistical in nature, they can be automated, and there will not be a need for a data scientist in the future.

What is the future of data science in next 10 years? ›

The future of Data Science jobs will look like the middleman who can communicate with computers and humans. AI and Machine learning are just tools that a data scientist uses to deal with big data. Data Science and Machine learning go hand in hand.

What is the future of data science in next 5 years? ›

Over the next five years, we'll see more and more specialized tools that are targeted at certain industries. For example, if you're a data scientist working with health data, you'll have access to a suite of analytics tools tailored to your industry. This will lead to better insights and more accurate predictions.

What is the highest salary for data scientist in Singapore? ›

SGD 18,500
  • SGD 18,500 /mo. Data Scientist.
  • SGD 23,000 /mo. Senior Data Scientist.
  • SGD 31,000 /mo. Lead Data Scientist.

How much does a fresh graduate data scientist earn in Singapore? ›

The average data scientist salary in Singapore is S$81,400 per year or S$35.58 per hour.

What is the basic salary of data analyst in Singapore? ›

Entry-level positions start at S$42,000 per year, while most experienced workers make up to S$90,000 per year.

Is there a demand for data scientists in 2023? ›

Tech companies will continue looking for secure candidates to fill their data scientist roles in 2023. The niche skills data scientists possess and the current skillset-driven market creates competition to find qualified candidates within the tech space. This means employees currently have the upper hand.

Can I start data science career at 30? ›

However, there's no reason why individuals can't begin work in data science later in their careers. In fact, it may even have its own unique benefits. Read on for five reasons why there's never a wrong time to learn data science.

Can I become a data scientist in 3 years? ›

Why not? You can become a Data Scientist the moment you acquire all the necessary knowledge and skills in the domain. You can start learning right now and self-learn a lot of the concepts from the internet. If you want to start learning coding for Data Science, you can start with Python.

Will data scientists be in demand in 2030? ›

According to the United States Bureau of Labor Statistics (2021), the field of data science and computer information research is predicted to develop at a rate of 22 percent from 2020 to 2030, which is three times faster than the typical profession.

How fast can I be a data scientist? ›

On average, to a person with no prior coding experience and/or mathematical background, it takes from 7 to 12 months of intensive studies to become an entry-level data scientist.

Is it hard to land a job as a data scientist? ›

How To Land an Entry-Level Data Science Role. It can be challenging to land an entry-level role, but it's not impossible. If you know what to do and who to reach out to, you'll have your first interview in no time.

How much does a mid level data scientist earn in Singapore? ›

The average National University of Singapore Data Scientist (Mid) salary in Singapore is S$6,660. Data Scientist (Mid) salaries at National University of Singapore in Singapore can range from S$4,800 - S$8,300.

Can a data scientist earn 1 million dollars? ›

However, compensation for those data scientists who develop the “holy grail” of technical skills, investment knowledge and the ability to communicate with stakeholders “has ballooned over $1 million” annually, Pook said.

How much does a junior data scientist earn in Singapore? ›

The average salary for a Data Scientist (Junior) at Singapore Pools is S$5,100 per month in Singapore, which is 24% lower than the average market salary of S$6,750 per month.

Who is No 1 data scientist in the world? ›

Yann LeCun. Dr. Yann LeCun is a professor of computer science and data science at New York University and the chief AI scientist at Facebook. He has made significant contributions to deep learning and computer vision and developed the Convolutional Neural Network (CNN), which is widely used in image recognition.

Which country has shortage of data scientist? ›

Finland. Finland has for years been at the center of the continent's technology industry. Yet the country appears to face a major shortage of individuals skilled in data analysis and science.

Which country is cheapest to study data science? ›

The cheapest countries to study data science are India, Norway, Norway, Germany, Japan, Denmark, and Finland are less expensive.

Which company hires most data scientist? ›

While many tech companies are laying off roles such as recruiters or designers, pros who have skills with data science tools tend to stay employed.
  • Varsity Tutors. ...
  • KPMG Accounting and Professional Services. ...
  • Amazon and AWS. ...
  • Info Way Solutions. ...
  • Microsoft Technology. ...
  • Capital One Finance and Banking. ...
  • Accenture.
Feb 3, 2023

What is lowest salary of data scientist in USA? ›

Despite a recent influx of early-career professionals, the median starting salary for a data scientist remains high at $95,000. Mid-level data scientist salary. The median salary for a mid-level data scientist is $130,000. If this data scientist is also in a managerial role, the median salary rises to $195,000.

Is USA best for data science? ›

The United States is one of the top destinations when it comes to pursuing a STEM program. It is an ideal study abroad country among the international students who want to study data science programs.

Why are data scientists quitting? ›

Lack of Professional Development Opportunities

Data science is a growing field. This means that the demand for data science specialists is increasing. At the same time, new opportunities and challenges are arising within the field, creating the need for data science professionals to keep up.

Is AI going to replace data scientists? ›

Most experts agree that it isn't likely that machine learning-based tools will be able to carry out these functions at the same level as humans any time soon. It's likely that businesses and other organizations will still have a need for humans who are experts in this field for some time to come.

Will data science be in demand in 2026? ›

In fact, data science has emerged as one of the fastest-growing business segments, having witnessed over 650% growth since 2012, and expected to grow to 230.80 billion dollars by 2026. This has significantly increased employment opportunities in the space and the demand for skilled resources.

How stable is data science as a career? ›

Growing Demand

Data science remains a career on the rise, consistently regarded as one of the most in-demand fields for much of the past decade, and this shows no sign of slowing down at all. In fact, the U.S. Bureau of Labor Statistics (BLS) projects a 36% growth in data science occupations through 2031.

Will there be a shortage of data science jobs in the next 5 years? ›

Studies estimate that the Data Science industry will grow by at least 2x over the next five years. The growth will further be accelerated by certain changes that will impact the career fundamentals for data scientists. The biggest change that will happen in the Data Science industry is the roles.

Is data science stressful? ›

Several data professionals have defined data analytics as a stressful career. So, if you are someone planning on taking up data analytics and science as a career, it is high time that you rethink and make an informed decision.

How long will data science be in demand? ›

Data scientist jobs are predicted to experience 36 percent growth between 2021 and 2031, according to the US Bureau of Labor Statistics [2]. Operations research analyst (or data analyst) jobs are projected to grow 23 percent [3]. Due to the high demand and technical skill set, jobs in data science tend to pay well.

Does data science require coding? ›

Coding is required. For working professionals who code: Coding is required in Data Science, and you can pick it up. There is a learning curve in Data Science because, along with code, you will also need to unlearn and relearn mathematics and business. The data science bootcamp can help here.

Is data science a secure job? ›

Data science is a safe career because it continues to be one of the most high-demand jobs today. This field of study is likely to stay despite the automation advancement as scientists continue to develop better technology and perform judgments that no automation in the world can do better.

Which field has highest salary in Singapore? ›

6 Highest Paying Jobs in Singapore and Why They Deserve It
  • General practitioners and medical specialists. ...
  • Sales manager. ...
  • Financial services manager. ...
  • Technical and engineering services manager. ...
  • Transport business development manager. ...
  • Industrial and production engineers.

Which job pays the most in Singapore? ›

Top 10 highest paying jobs in Singapore
  • C-suite roles. It is not surprising that executive positions are among the highest paying jobs in Singapore. ...
  • Partner at an international firm. ...
  • Regulatory Affairs Director. ...
  • General Counsel. ...
  • Head of Sales. ...
  • Head of Investment Banking. ...
  • Head of Compliance. ...
  • Head of Procurement.
Jul 2, 2022

Which degree pays the most in Singapore? ›

The Highest Starting Salary Degrees is at NTU
1NTU Double Degree in Business & Computer Engineering/ Computing$6,300
2NUS Computer Science$5,800
3SMU Law$5,500
4NUS Law$5,150
8 more rows
Mar 16, 2022

How much does a full stack data scientist earn in Singapore? ›

Average Annual Salary: According to various renowned websites, the average salary of a data scientist in Singapore is SGD 104,574.

Is data science a happy career? ›

Data science is a fantastic career with a tonne of potential for future growth. Already, there is a lot of demand, competitive pay, and several benefits. Companies are actively looking for data scientists that can glean valuable information from massive amounts of data.

Which country pays highest salary to data analytics? ›

On average, the US typically pays the highest data analyst salaries, followed by countries including Germany, Australia, the Netherlands, and Canada.

Is data analytics in demand in Singapore? ›

The Data analysts are in-demand in the Singapore job market. They are needed to collect and analyse data to find trends and patterns that can be used to make business decisions.

Can you make 100k as a data analyst? ›

Candidates with advanced skills or at least three years of work experience on their resume can earn an average salary of over $100,000 per year.

Is data science a good career in 2025? ›

Therefore, there is a need for a data scientist in every industry. Self-analysis is vital if any business needs to grow and stand out. A data scientist does this analysis. So, the job of a data scientist is very high in demand and will remain as such in the near future.

Will data science exist in 10 years? ›

In 10 years, data scientists will have entirely different sets of skills and tools, but their function will remain the same: to serve as confident and competent technology guides that can make sense of complex data to solve business problems.

Is data science dead in 10 years medium? ›

So, until and unless we find a way to not use data itself, data science as a field is not going to be obsolete anytime soon. However, many believe that since a data scientist's daily tasks are quantitative or statistical in nature, they can be automated, and there will not be a need for a data scientist in the future.

What is the fastest way to become a data scientist? ›

How to become a data scientist
  1. Earn a data science degree. Employers generally like to see some academic credentials to ensure you have the know-how to tackle a data science job, though it's not always required. ...
  2. Sharpen relevant skills. ...
  3. Get an entry-level data analytics job. ...
  4. Prepare for data science interviews.
Nov 14, 2022

Is 50 too old to become a data scientist? ›

You can become a data scientist at any age if you're willing to put in the work.

What is the maximum age to be a data scientist? ›

1. Designation: Data Scientist Max Age Limit: Not more than 45 Years as on the last date of receipt of application.

Why so many data scientists are leaving? ›

Lack of Professional Development Opportunities

Data science is a growing field. This means that the demand for data science specialists is increasing. At the same time, new opportunities and challenges are arising within the field, creating the need for data science professionals to keep up.

Will data scientist be replaced by AI? ›

Long answer short —AI models like Chat GPT can be a valuable tool for data scientists, but they cannot replace the important role that data scientists play in various industries. This is true for most of the roles.

Why not to become a data scientist? ›

Stressful work environment – They usually experience stressful work which can result in burnout and reduced productivity. Disconnected from goals and vision – The objectives, vision, and mission of the scientist do not resonate with the company. Thus, they are unable to interact and get disconnected.


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