How to Become a Data Scientist in Singapore

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:

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.

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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].

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.

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.

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:

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 Coding – Python 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.

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.

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.

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