5 Characteristics of Data Scientists

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A Successful Data Scientist Should Have These Characteristics

  • Analytical Skills
  • Strong Sense of Logic
  • Superior Mathematical Ability
  • Orientation to Detail
  • Ingenuity

Understanding the top five characteristics of great data scientists helps a person decide if this is the right career for them. Data science professionals overlap with statisticians, data engineers, information research scientists, and similar occupations. These are the characteristics a good data scientist needs to do the job well and have a rewarding career.

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1. Analytical Skills

Analytical SkillsData science involves a lot of analysis. A great data scientist must be able to:

  • collect information
  • organize it
  • code it
  • analyze it

From the analysis, the data scientist needs to be able to draw a conclusion. They should be able to document their work in a way that would allow the process to be repeated with the same result. A data scientist should also be familiar with a wide range of statistical methods, tests and software programs or applications for conducting analytic activities. They might use different machine learning algorithms.  A great data scientist is also organized in their thinking. Their critical thinking skills help guide them toward the right tools and techniques.  They take the orderly steps in getting from an idea to a conclusion without skipping any essentials.

2. Strong Sense of Logic

Data scientists must have a strong sense of logic and reasoning. When data scientists write a computer program or write code for analyzing the data that they collect, they have to write it in a particular order for the computer to process correctly. They should also be able to document what they did and why they did it as comments in the code. Another data scientist should be able to review the logic created and understand why it was written in that way. Data science professionals should also be efficient in their logic and reasoning, creating solutions that do not require excessive computational resources for the problem.

3. Superior Mathematical Ability

Superior Mathematical AbilityAn effective data scientist should have a superior mathematical ability. They should have strong skills in multiple areas of mathematics, including:

  • algebra
  • statistics
  • data cleaning
  • mathematical theory
  • data processing

Data professionals may also need to be good at other types of technical skills, such as creating computer programs that instruct the computer on how to perform a certain type of analysis. This might include the use of statistical software packages or certain computer languages.  These skills are critical when working with big data.

4. Orientation to Detail

According to the Bureau of Labor Statistics, another essential characteristic of a data scientist is an orientation to detail. A scientist of data should be able to spot an anomaly with ease. They should be attuned to unusual results. They should also be able to proofread and debug their own computer programs because one error can lead to a major difference in a data analysis project.

5. Ingenuity

Data science professionals need to excel at finding innovative solutions to problems. They also need to have persistence. In many cases, the first proposed solution or algorithm may not work as intended. The data scientist would have to create a new way of working on the problem. That new way might test their skills and require them to learn something new, such as a new statistical test of significance or a new line of code.

Conclusion

An effective data scientist will also have a passion for learning and discovery. Data scientists need to be able to communicate well with their superiors and colleagues. Each of these five characteristics of effective data scientists increases the person’s chances at enjoying what they do and being good at it.

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