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Big Data Creates Big Opportunities for Data Science Professionals

May 31, 2019, 16:53 PM by Ching Shen Chew
Data Scientist vs. Data Analyst: what’s the difference?

It’s a good time to be in data science, and even better if one happens to be in Singapore.

  • Data scientist tops the list of emerging jobs in Singapore with the fastest growth rate of 17 times, from 2013-2017. *
  • Data analytics industry contributes at least S$1 billion annually to Singapore's economy. **
  • Singapore is hosting Facebook’s first data centre in Asia, which will “support hundreds of jobs”, as per the social networking leader. +

Clearly, Singapore is leading the big data revolution in Southeast Asia, and with good reason.

Why is Singapore at the forefront?

Besides its long-standing efforts to become a digital-first economy, Singapore also has:

1. The fastest Internet speed in the world: Singapore has a mean download speed of 60.39 Mbps, as per Broadband Speed League 2018.
2. A supportive ecosystem: We have a thriving business ecosystem with a well-developed IT infrastructure and supportive government policies.
3. Increasing number of companies using big data: Not just finance, businesses in manufacturing and healthcare sectors are also leveraging big data.

Not just the top emerging job, data scientist is also the most in-demand one in Singapore. Which brings us to the question:

What does a data science professional do?

A data science professional interprets gobs of data and uses these data-driven insights to anticipate and counter business challenges. 

What does it take to be a data science professional?

To be a competent data science professional, one needs to have:

  1. Strong base in mathematics, statistics and computer science
  2. Knowledge of multiple programming languages
  3. Insatiable desire to mine data for new insights
  4. Communication skills to simplify findings

One needs to add to these skills, depending on one’s job. While data science offers numerous job opportunities, they can be broadly categorised into data scientists and data analysts.

Data Scientist vs. Data Analyst: what’s the difference?

The roles can be overlapping, with experienced data analysts often filling in as data scientists in start-ups. However, they are distinctly different in a few ways:

Data ScientistData Analyst
Collects and analyses data, establishes patterns, experiments with the data, and conveys the results in understandable formatsAnalyses data, and represents their insights visually with charts and graphs
Should have advanced degrees, such as a Master’s or a PhD in relevant fieldsAdvanced degree is not a necessity

On average, a data scientist earns more than a data analyst.

Want to be in data science?

Click on the link below to access our list of courses and search with the word ‘data’ to locate our multiple courses on data analytics and data science. In case of any queries, do ping us on Facebook


*Singapore Emerging Jobs Report by LinkedIn


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