Prospective Data Scientist, Yuk Master This To Be Seen By Today’s Companies

The development of technology in the world has been the influence of data.  Data describes a representation of facts arranged in a structured manner. With data Researchers can create technologies where they can do something based on existing data such as AI, Machine Learning, and others.

In today’s era, the tight competition in finding work is no stranger to being heard by our ears. Good for those who have tried college or not.

Why did that happen? Because now, not only the employment is few, but also the standard of work is already high. Therefore, all the job applicant must do is prepare himself well in order to compete with other job seekers. The increasing number of job applicants who apply for jobs makes a company agency raise the level of quality of workers it seeks.

After graduating from college, students will enter the world of work. Quoted from the Central Statistics Agency (BPS) in February 2021 in Indonesia there are 139.81 million people who are ready to work. In Indonesia itself there are still not many people who are steeped in the science that becomes the prima donna of many digital companies, although not many people are steeped in data science but 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 DQLab recruiters:

1. Multiply Your Experience

Experience is important if you want to start a career as a Data Scientist. Start looking for projects related to Data Science that are large or small scale.

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

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

Also read Belajar Data Science Secara Otodidak? Berikut langkah-langkahnya!

2. Attitude

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

Including manners in acting, or speaking. Ethics are also described by the good or bad attitudes and behaviors of a person implemented in everyday life.

Therefore, someone who has good ethics, will definitely have a good impact on his environment. And, what is needed by companies are those who have good ethics, in order to work in accordance with what has been assigned and can work with the team.

3. Master Softskill and Hardskill Data Scientist

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.

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:

• Data Analysis

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 language

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.

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

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.

• Cooperation

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.

• Critical Thinking

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.

Also read Mulai Belajar Data Science GRATIS bersama DQLab selama 1 Bulan Sekarang!

4. Follow the Available Data Scientist Course, One of Them 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 on DQLab you can develop your skills in Data Scientist and also meet new people who share similar interests. DQLab also provides materials offered complete and in accordance with the needs of the industry, compiled by competent mentors in their fields from unicorn companies and startups.

By Yohanes Ricky & Annissa Widya | DQLab

Kuliah di Jakarta untuk jurusan program studi Informatika| Sistem Informasi | Teknik Komputer | Teknik Elektro | Teknik Fisika | Akuntansi | Manajemen| Komunikasi Strategis | Jurnalistik | Desain Komunikasi Visual | Film dan Animasi | Arsitektur | D3 Perhotelan | International Program, di Universitas Multimedia Nusantara. www.umn.ac.id