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5 Differences Between A Data Analyst & A Data Scientist

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Data Analysts are one of the most in-demand jobs in Singapore today. While there is definitely a lot of interest in data professionals, the distinction between a data analyst and a data scientist might not be clear since both positions deal with information, but in different ways. Before we talk about the differences, some of you might still be confused on what exactly is a data analyst and a data scientist.

A Data Analyst gathers information in order to spot trends that might assist corporate businesses in making tactical decisions. They mainly focus on conducting statistical analyses to answer queries and solve issues whilst converting their findings. Moreover, a data analyst typically works as a part of an interdisciplinary team to determine the organization’s goals.

Meanwhile, a Data Scientist is more involved in the design of data modeling procedures, developing algorithms and predictive models. As a result, data scientists devote more time and effort into developing tools, automation systems and data frameworks. A data scientist, as opposed to a data analyst, focuses more on inventing new tools and methods for extracting the information needed by the company to tackle complicated problems.

Now that you have a bit more of an idea of the two mentioned, let us dive into 5 differences between a data analyst and a data scientist:

1. Education

To become a data analyst or a data scientist, there is no particular educational qualification required. However, it would be beneficial to obtain at least a bachelor’s degree in a quantitative field like mathematics, statistics, computer science, engineering etc. To grow your data scientist career in a prestigious company and receive a high pay, a masters or doctorate degree is necessary. However, a bachelor's degree will be beneficial for a data analyst.

2. Roles and Responsibilities

The role and responsibilities of a data analyst and a data scientist vary based on the sector and area where they work. Nevertheless, a typical day for a data analyst can include determining how or why something happened, for example, determining why sales plummeted. On the other hand, data scientists are more interested in what will or may happen in the future.

3. Skill Comparison

Both data scientists and data analysts work with data, but each role’s skills and tools are slightly different. Data scientists mainly use programming languages but data analysts use SQL or Microsoft Excel. To better understand the comparison:

Data Analyst Skills

Data Scientist Skills


​Python, R, JAVA, Scala, SQL, Matlab, Pig

Using MS Excel to analyze data and Tableau to create reports.

Uses Tableau and Power BI to visualize data and tell stories.

Data Wrangling

​Data Wrangling and Data Modeling

​Statistical and probability concepts are well-understood.

A solid understanding of calculus, linear algebra, statistics, and probability is required.

​Analyzing exploratory data

​Cloud computing and machine learning

4. Salary

Depending on the sector and place of employment, the salary of a data analyst and a data scientist may vary. A data analysts’ average salary can range from $63,377 to $84,000, while the average salary for data scientists can range from $79,423 to $162,000. According to a report by Indeed, data analyst jobs will see a 20% growth from 2018 to 2028.

5. Career growth

In the beginning, as a data analyst, you may start your career in an entry-level role where you'll mainly be reporting analytical data and creating dashboards. In due course, you can upgrade your skills and take up a managerial role, or even continue your education to sharpen your skills.

Companies currently see a skill gap in the role of a data scientist, where there are more open positions than there are skilled professionals to fill them. To position yourself for more advanced and high-paying data scientist roles, getting a masters and doctorate degree is highly encouraged.

We hope this blog has helped you understand the differences between a data analyst and a data scientist, so that you can pick the right career path according to your interests and background.

Information extracted:

2U.INC. (2021). Data Analyst VS data scientist. Master's in Data Science. Retrieved November 12, 2021, from

Software Testing Help. (2021, November 1). Data Analyst VS data scientist - what are the key differences. Software Testing Help. Retrieved November 12, 2021, from


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