Skills That Data Scientists Should Have
Minister of Education and Culture Nadiem Makarim stated that currently the workforce must have soft skills and hard skills that are in accordance with the work they choose to be easily glimpsed by the business world and the industrial world. Especially when you want to become a Data Scientist, where the profession is a multidisciplinary science that requires many soft skills and also hard skills.
Basically, every profession requires meeting soft skills and hard skills that are balanced. Both of these are basic points that must not only be known, but must also be owned by job seekers. In fact, you who have entered the world of work of course learning to explore these two things can increase your value. Here are the skills you can learn to get recruiters interested in you.
1. Hard Skills a Data Scientist Needs
Hard skills are the skills needed for a job. This is usually written in the requirements column in a job opening. Hard skills are usually specific skills and become one of your job descriptions later. Hard skills needed by a Data Scientist include:
Often data scientists will retrieve data from a database using SQL queries, pivot tables with microsoft excel or use similar software such as SPSS. Data Scientists must also master programming languages because programming languages can help in creating data visualization in the form of graphs.
From the analysis of data data is also expected to be able to test and also provide suggestions or solutions based on the findings that have been tested. Thus, it can increase satisfaction and service to customers. This analysis can also aim to be a preventive measure of the company in order to create a data series of problems experienced by the company.
* Mathematics and Statistics
Mathematics is one of the sciences that has many uses and benefits in everyday life. Almost every aspect of man uses mathematics in trading, carpentry, and more.
As a Data Scientist you will certainly struggle with millions of data and that makes mathematical and statistical skills indispensable. In data processing there are algebraic operations, matrices, and regressions. If a Data Scientist does not master this science will certainly be a very big obstacle, because not only can not process data but you also can not interpret numbers into data instruments such as graphs, tables, and other graphic elements.
Programming languages are crucial for a data scientist. With the program language you can perform numerical analysis, and statistics with large data sets. SQL (Structured Query Language) is a program language designed to manage data in relational databases and is currently the most commonly used method for accessing data in databases.
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2. Soft Skills a Data Scientist Needs
On the other hand, soft skills are personality, personal attributes, and communication skills needed to succeed in a job. It’s good that your soft skills show how you interact with the environment around you. Soft skills needed by a Data Scientist include :
Communication becomes the key to a good Data Scientist, as well as data scientist in managing data but if he can not convey the information to others then the data processing will not be maximal.
A Data Scientist is the first door of data, there are still later stages after the completion of the Data Scientist task. Therefore, working with teams from other divisions is what is needed so that there is no miss perspective.
As a data scientist, data analysis is very important in the business world. All plans and decisions must be based on the rational reasons that follow them. That way the right analysis then the company can better understand the problems that the company will probably experience and better understand the market.
Based on the experience of Senior Data Scientists, they concluded that Data Scientist is a Big Data process that seeks to provide meaningful information from large amounts of complex data using various tools, algorithms, and other principles.
3. Transferable Skills Needed by a Data Scientist
These skills may be heard less frequently than soft skills and hard skills. Transferable skill itself is a person’s ability that can facilitate him in undergoing the world of work because it can be used in various types of industries or careers. Transferable skill is a combination of soft skills and hard skills. This skill is learned through experiences during your life that are useful for the future. This skill can also be included in soft skills. Examples of transferable skills are also similar to soft skills.
Transferable skills are useful for those of you who want to change careers that are completely irrelevant to your previous job. Many companies also include this transferable skill in the criteria for accepting employees. Transferable skills required by a Data Scientist are:
* Digital LiteracyThis ability is important because every day technology is certainly increasing, your ability to adapt to the latest technology and can operate existing tools and tools can show that you are deft and easily adjust to the job.
* Data Research and AnalysisThe profession of Data Scientist itself is also very dependent on digital technology that can present so much data with an infinite amount of information. Therefore, data research and analysis skills are also skills that you should develop and also have if you want to become a Data Scientist.
* Thoroughness of DetailWith the amount of data analyzed every day by Data Scientist, of course, if the wrong data input will have an impact with the results that will come out and result in the results of the analysis become inaccurate. The importance of being thorough in completing tasks can show that you have high professional standards and do not need to be supervised at all times.
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By Yohanes Ricky & Annissa Widya Davita | DQLab
Kuliah di Jakarta untuk jurusan program studiInformatika|Sistem Informasi|Teknik Komputer|Teknik Elektro|Teknik Fisika|Akuntansi|Manajemen|Komunikasi Strategis|Jurnalistik|Desain Komunikasi Visual|Film dan Animasi|Arsitektur|D3 Perhotelan|International Program, diUniversitas Multimedia Nusantara.