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Job trends of Data Science in Hong Kong

By Vahid Haghzare, Director Silicon Valley Associates Recruitment &

Victor Chen, Senior Recruiter, Silicon Valley Associates Recruitment

One of the top IT Recruitment Agencies in Hong Kong, Dubai, Shenzhen, Shanghai, Singapore, and Japan, SVA Recruitment is an IT and employment agency that provides jobs, executive search, and recruitment services.

Due to the high demand for data science jobs, many consider switching careers in this field. As a result, data science careers in Hong Kong, Singapore, China, and the Asia Pacific have shown significant job trends in various levels of categories.

As of 2021 salary trends, Silicon Valley Associates Recruitment presents a comprehensive Salary Guide in IT and Technology recruitment in Hong Kong, Singapore, and Shenzhen, China. Some of its highlights about Data Scientist Salary are as follows:

Data Scientist jobs in Singapore have a monthly salary ranging from 8,000 SGD to 16,000 SGD. The Average Monthly Salary is 12,000 SGD.
Data Scientist jobs in Hong Kong have a monthly salary ranging from 20,000 HKD to 60,000 HKD. The Average Monthly Salary is 35,000 HKD.
Data Scientist jobs in Shenzhen, China has a monthly salary ranging from 25,000 CNY to 50,000 CNY. The Average Monthly Salary is 32,000 CNY.

What it takes to Pursue a Career in Data Science

To become eligible in pursuing Data Science careers, you have to clearly understand what it takes to become one. Knowing its foundation is a good start.

The Pillars of Data Science

Mathematics/Statistics: Pursuing data science requires you to have significant knowledge of Mathematics because this field is purely based on statistics and probability.
Computer Science: Since data science jobs have to work on data, they have to use computers all day. Any field in data science requires you to have proficiency with coding languages and computer programming knowledge. Data Science, without familiarity with coding experience or knowledge, can be a bit difficult.
Business Knowledge: Data Science utilized data to make business decisions. It means that you have a strong business acumen that is required in pursuing a data science career.
Communication: Working in a data science job requires you to work with a team of people to make the job done. That is why excellent communication skills are a huge requirement in this field and even in most other fields.

Some of the Most Preferred Degree Courses:

Bachelor’s Degree in Engineering
Bachelor’s Degree in Computer Science
Bachelor’s/Master’s Degree in Science
Degree in Mathematics, Applied Mathematics, or Statistics

These courses are just some of the preferred educational requirements in pursuing a career in data science. Some people who do not have a direct degree in data science but want to explore the field often take boot camps that are related to courses like coding, data science, and machine learning. Virtually all data scientists have graduated from an institution of higher education. This includes bachelor, Masters's, MBAs, and Ph.Dss. Nonetheless, Ph.D. is not a requirement for the job but a bonus.

However, some degrees seem to be much more popular than others. Computer Science is the most well-represented degree among data scientists. This isn't a complete shock since good programming skills are essential for a successful career in the field. It's not all that surprising that a degree in Statistics or Mathematics is among the top preferred courses. At the end of the day, it’s all about having the right skills and landing in the right role.

Data Science Terms you Need to Know

Data Science is an umbrella term for all the following terms:

Algorithms: An algorithm is a set of instructions we give a computer so it can take values and manipulate them into a usable form.
Big Data: Big data is more about strategies and tools that help computers do complex analyses of very large data sets. Since processing huge data is challenging, it requires you to use special techniques and tools to accomplish computations.
Data Mining: The process of examining a set of data to determine relationships between variables that could affect outcomes – generally at a large scale and by machines. They use numerous techniques to accomplish this task such as regression, classification, cluster analysis, and outlier analysis.
Machine Learning: A process where a computer uses an algorithm to gain understanding about a set of data, then makes predictions based on its understanding. It helps computers predict outcomes without explicit human input.
SQL: An acronym that stands for a structured query language, this programming language is designed to interact with databases.
Statistics: The entire set of tools and methods used to analyze a set of data, process data mining, and machine learning algorithms. Statistics has various statistical tools that data professionals use to reason and communicate information about their data. Some of the most basic and vital statistical tools include correlation, median, sample, standard deviation, and statistical significance.

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Silicon Valley Associates is ideally positioned to support the continual demand from tech companies and IT Departments looking to hire in Hong Kong, Asia, and Worldwide. Please let us know if you would further advise on the above topic or your hiring needs