4IR Technical Center

The development of technology in the world has been the influence of the existence of data. Data describes a representation of facts that are structured in a structured way. With the data, researchers can create technology where they can do things based on existing data such as AI, Machine Learning, and others.

In today’s era, intense competition in finding work is not something that is foreign to our ears. Good for those who have tried college or not.

Why did it happen ? because now, not only are there few jobs, but also the standard of work is already high. Therefore, what must be done by job applicants is to prepare themselves well so that they can compete with other job seekers. The increasing number of job applicants who apply for work makes a company agency raise the level of quality of the workers it is looking for.

After graduating from college, students will enter the world of work. Quoted from the Central Statistics Agency (BPS) in February 2021 in Indonesia there were 139.81 million people who were ready to work. In Indonesia itself there are still not many people who study science which is the prima donna of many digital companies, although not many people have studied Data Science, companies are also looking for the best candidates to be able to improve company performance.

Here are tips to make you look attractive in the eyes of recruiters a la DQLab:

1. Expand Your Experience

Experience is essential if you want to start a career as a Data Scientist. Start looking for projects related to Data Science, whether large or small.

This experience will certainly be useful if you want to continue your career as a Data Scientist in a large company. By working on a small project, the company can see how responsible you are in working on a project even if it is a small project.

Experience can be the foundation in building your portfolio, not only that by increasing experience you can practice the techniques you have learned in the learning stage. The portfolio is also proof that you do have an interest and are also committed to honing your skills as a Data Scientist.

Also read: Self-taught Data Science Learning? Here are the steps!

2. Attitude

Academic quality and a lot of experience in organizing will be in vain if your attitude or attitude is nil. Being someone who is polite and works hard remains the main value in a person. Especially with the very development of technology where everything we do can be recorded and can be shared on social media.

Including politeness in behaving, or speaking. Ethics is also described by the good or bad attitudes and behavior of a person who is implemented in everyday life.

Therefore, someone who has good ethics will definitely have a good impact on the environment. And, what companies need are those who have good ethics, so they can work according to what has been assigned and can work with a team.

3. Master the Softskill and Hardskill of Data Scientist

Basically, every profession requires a balance of soft skills and hard skills. These two things are basic points that not only must be known, but also must be owned by job seekers. In fact, those of you who have entered the world of work, of course, learning to explore these two things can increase your value.

Hard skills are abilities needed for a job. This is usually written in the requirements column of a job vacancy. Hard skills are usually specific abilities and become one of your job descriptions in the future. The hard skills needed by a Data Scientist include:

  • Data analysis
    Often a Data Scientist will retrieve data from a database using SQL queries, pivot tables with Microsoft Excel or using similar software such as SPSS. Data scientists must also master programming languages ​​because programming languages ​​can help visualize data in graphical form.
    From the analysis of company data, Data Scientist 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 company’s preventive action so that it can create a data series of problems experienced by the company.
  • Mathematics and Statistics
    Mathematics is a science that has many uses and benefits in everyday life. Almost every aspect of human use of mathematics in trading activities, carpentry, and much more.
    As a Data Scientist you will of course be dealing with millions of data and that makes math and statistics skills indispensable. In data processing, there are algebraic, matrix, and regression operations. If a Data Scientist does not master this knowledge, it will certainly be a very big obstacle, because not only cannot you process data but you also cannot interpret numbers into data instruments such as graphs, tables, and other graphic elements.
  • Programming language
    Programming language is crucial for a Data Scientist. With programming languages ​​you can perform numerical analysis, and statistics with large data sets. SQL (Structured Query Language) is a programming language designed to manage data in relational databases and currently this method is the most frequently used method to access data in databases.
    On the other hand, soft skills are the personality, personal attributes, and communication skills needed to succeed in a job. It’s good that the soft skills you have show how you interact with the environment around you. Soft skills needed by a Data Scientist include:
  • Communication
    Communication is the key to a good Data Scientist, the best is a Data Scientist in managing data, but if he cannot convey this information to others, then the data processing will not be optimal.
  • Cooperation
    A Data Scientist is the first door of data, there are still further stages after the completion of the Data Scientist task. Therefore, collaborating with teams from other divisions is necessary so that there is no miss perspective.
  • Critical Thinking
    As a data scientist, data analysis is very important in the business world. All plans and decisions must be based on rational reasons that follow. With the right analysis, the company can better understand the problems that the company might experience and better understand the market.

Based on the experience of Senior Data Scientist, they conclude that Data Scientist is Big Data processing that seeks to provide meaningful information from large amounts of complex data using various tools, algorithms, and other principles.

Take the Available Data Scientist Courses, One of them is DQLab UMN

As a Data Scientist, of course, data processing is a basic skill for you to become a Data Scientist. By following the courses available at DQLab you can develop your skills in Data Scientist and also meet new people who have the same interests. DQLab also provides materials that are offered completely and according to industry needs, compiled by competent mentors in their fields from unicorn and startup companies.

By Yohanes Ricky& Annissa Widya


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