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Essential Knowledge and Skills of Data Scientist

They called as Data Scientist because mostly they are highly educated people, with very strong educational background that necessary to develop the depth of knowledge in specific field of their expertise - with 88% of them have at least Master's degree and 46% have PhD. The Data Scientist must mastering broad field of knowledges and skills, including strong fundamental in mathematics and statistics, programming, communication and etc., which will be discussed further in this section.

Theoretical Knowledge

a. Mathematics

Mathematics is a core fundamental knowledge of any contemporary discipline of science, including data science. Mastering the foundational mathematics is necessary for Data Scientist, so they can properly apply the suitable techniques and methods based on requirement. Solid understanding in mathematical method, such as differential equation, numerical method and etc., which encoded behind the cool algorithm help a lots in creating meaningful product recommendation for the client. Well equipped with this knowledge make them more confident of using required tools to do the work, such as using Python for Machine Learning, and capable to customise it according to the needs and requirement.

b. Probability & Statistics

Another fundamental knowledge that must be mastered by a data scientist is Statistics. Statistics is one of powerful fundamental knowledge or field of study that able to give us the concrete conclusion on the data rather than guessing. The statistical findings could provide strong evidence and increase the level of confidence for making any technical or business decision.

Technical Skills in Computer & Programming

Advancement of computing technology has accelerate the process of analysing mass amount of data, thus improve the efficiency in term of processing time and accuracy of the result. It has bring huge advantages to the field of data science, and about 90% of the total work are conducting using computer. Specific task required specific computer skill. For example, developing machine learning algorithm require programming skill using languages such as Python and R. Creating visualization for result presentation may require knowledge in specific software such as Tableau, Power Bi and etc. By having multi-set of skills in programming languages and software give lots of advantages for the data scientist to perform their work faster and high accuracy. List of computer and programming skills that are important in data science are such in the list below:

a. Python & R Programming

b. Hadoop for big data processing.

c. MySQL for database

d. Machine Learning & Artificial Intelligent

e. Data Visualization & Business Intelligence.

Specific Knowledge Domain in Businesses and Industries

Good understanding and knowledge on specific business domain is another important criteria that should be mastered by data science consultant or data scientist. They must be able to communicate their statistical findings and predictive result in effective way to their client. Most of business clients do not have interest in technical jargon, but they prefer to be briefed on information such as:

  • What will be the impact on the sales projection after increasing the marketing budget for targeted region?

  • What might be the significant factor (s) that affect the productivity of employees in the organization.

Basically, individual at managerial position having good skill in business communication. Thus in a team of data science project, it is a good advantages if they are comprises of group of individual that having multiple skill, such as mathematic, statistics, programming, visualization and business communication.

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