How to Become a Data Scientist – Job Description

Job as a data scientist – working in data science

In times of artificial intelligence, machine learning and digital change, a new job description has established itself and it is becoming increasingly popular. The data scientist was named “Sexiest Job in the 21st Century” by Harvard Business School. As you can see, the digital transformation stops at nothing and there are always new possibilities.

EnİyiMeslekler shows you what the data scientist’s job is, what skills he should bring and what his salary looks like

Are you looking for a job as a data scientist? On EnİyiMeslekler you will receive free job offers and job inquiries from employers looking for data scientists.

Definition of “data scientist”

A data scientist uses practical knowledge and theoretical approaches from his studies to generate information from large amounts of data. He discusses this with the management level of a company and finds an optimal solution with it and the IT department to use this data.

He must be able to present these findings and be available to the company as a consultant in order to increase efficiency. With the sheer never-ending amount of data generated every day, it’s a job that will be even more important in the future than ever before.

Since these problems apply to many industries, you can of course apply for this profession for a large number of industries. The starting salary is also very high due to the high demand. If you specialize and have a few years of professional experience, you are one of the top earners in America.

“You ask yourself: How do I become a data scientist?”

On EnİyiMeslekler you can create your free job match and find out how good your skills are for your dream job as a data scientist.

What prerequisites and competencies are necessary to work as a data scientist?

With the amount of theoretical knowledge and different areas in which one has to solve problems, a doctorate is an often chosen basis to acquire the necessary knowledge and skills. Mainly you work with numbers and statistics, so you should have certain skills. An analytical understanding and a certain curiosity about information are important. Thinking in a problem-oriented manner and weighing up several proposed solutions as well as independent further thinking are essential requirements for working as a data scientist.

Soft skills are important for a later career. Soft skills include, for example, communication and leadership skills. In many conversations, you have to present your results without using technical terms. Advising the management level and playing a leading role in the strategic decisions of companies is also one of your tasks. The communication skills also come into play in the coordination between management level and IT departments.

You need knowledge in the areas of data analytics, data management, information design and communication, IT and corporate management. Database technologies such as SQL and the command of one or more programming languages ​​such as Java, C++, C# and R are added.

Training as a data scientist:

The basis for the profession of data scientist is a degree with a master’s degree or even a doctorate. The course of study is decisive in which area you want to work later. The most common courses of study are computer science, business informatics with mathematics, business mathematics or physics.

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Studying is not the only way. There are companies and commercial providers who offer further education and training. Such alternative training paths bring practical knowledge and practical experience as an advantage.

The competencies are now divided into must and can competencies, i.e. those that companies definitely require (must competencies) and those that make you successful in this profession (optional competencies).

Competencies Must:

  • Knowledge of big data
  • Knowledge of databases, Java, SQL
  • Knowledge of analytics, data management
  • Analytical thinking
  • Communication skills
  • Leadership skills

Competencies Can:

  • Patience and fun in solving complex problems
  • Curiosity about information and finding solutions
  • Presentation skills
  • Good grasp
  • Targeted work

Continuing education

You never really stop learning in life and that is especially true for your own professional life, because humanity never really stands still. Certain job descriptions change again and again and acquire a new task for which they need a special qualification.

So how do you stay on the ball and already know today what new tasks you will face tomorrow? Exactly: conferences! At these meetings of various specialists you can find out what the current development in your field of work looks like and where the journey is likely to take in the next few years.

That is why EnİyiMeslekler has selected the most prestigious and important certifications and conferences for the job of data scientist and listed them below:

What are the tasks of a data scientist?

A data scientist is primarily a consultant for a company. Accordingly, his tasks are, for example, strategic advice, problem solving, consultations etc. The coordination of the management level with the IT departments and internal communication between individual areas with a leading role are also fields of activity of the data scientist.

The knowledge with which the data scientist advises a company is based on the data that the company has collected. Choosing data sources and implementing data collection systems are the first tasks in the work of a data scientist. Then evaluate this data and create a hypothesis. A hypothesis has to be based on data again. Reducing and filtering the seemingly endless amount of data on the Internet is an essential task of the data scientist.

The main task of a data scientist is to write a report and to present the data with evaluation and hypothesis without subject-specific terms and to derive a recommendation for action. The ultimate goal is to increase the company’s efficiency. These are the learning contents during the training. Developing strategic questions and solution applications that serve as a basis for decision-making for the management level are based on the previously developed hypothesis.

Standard tasks are the maintenance and expansion or implementation of new data systems with the IT department.

In summary, the data scientist evaluates structured data in order to achieve better and more efficient business goals of companies.

How much does a data scientist earn?

The average gross salary of the data scientist is around $ 54,000 per year. It can be influenced by various factors. The size of the company, the location, the industry, the degree and the work experience play a role. The minimum and maximum salaries are between 38,500 $- 85,500 $ annually.

Work experience mainly plays a role here. With specializations in certain areas, including big data, with a few years of professional experience, top salaries of 120,000 to 160,500 $ gross per year are also possible at large companies.

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Here you can find out more about the starting salary and salary development of data scientists.

Summary > job profile data scientist:

How do I apply to be a data scientist?

As a data scientist, studying with a master’s degree or doctorate is recommended. Since he bears a lot of responsibility in advising the management level, professional experience is required in almost all cases. If you have specialized in an area, e.g. Big Data, you should definitely emphasize this during the interview.

A number of skills such as independent thinking, analytical thinking and communication and leadership skills are required. If many of the MUST competencies apply to you and you like the structure of a large company, you have a good chance of a job.

As a data scientist, you will find a job with a good starting salary in almost every industry. This little infographic shows you the current job market in the field of big data:

During the interview, you should name and emphasize any required skills you have. In addition, you can use a simple example to show that it is easy for you to explain complex issues with simple words and to present them in an understandable manner. Because this will also be one of your later activities.

You should look at the structure and history of the company. Show interest if someone tells you about it in the interview. Give an example by showing that you’re good at statistics. Curiosity and advice should be your strengths.

It can also be the case that smaller companies pay high salaries. Think about whether you should apply there and try to get your dream job.

You can find tips for salary negotiation for a data scientist in the career guide article Salary Negotiation.

Tips for applying to become a data scientist after training:

If you have already set priorities in your academic training as a data scientist and have concentrated on very specific tasks, then place a special focus on this in your application. In the application, concentrate on what suits you and the training content that you would like to continue to deepen later.

Another tip for your job search, to finish off: On EnİyiMeslekler you can create your free job match and find out how well your skills match your dream job. Here you can register for free and conveniently receive job inquiries from interesting employers.

Conclusion

The data scientist has a varied and exciting job. The most important information at a glance is now summarized in a compact form:

  • Data scientists take care of the extraction of information from a large amount of data and its analysis.
  • They support the company in an advisory capacity and bring management level and IT departments together. By analyzing the data, solutions are found for the company.
  • You can start your career through courses such as computer science, mathematics or physics. But you can also become a data scientist with further education and training courses in which you can gain practical experience.
  • Knowledge of big data, databases and data management as well as analytical thinking are very important skills in the job. Also helpful are good comprehension, patience and fun in solving complex problems.
  • The average salary of a data scientist is between 45,500 $ and 83,500 $ per year.

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