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Data Scientist (m/w/d)
"We are generating more and more data, digitizing more industries and processes, and markets are becoming more and more competitive - so the need for data scientists is only going to grow." - Olga Kostova, data scientist and conversion optimization specialist"
In a highly digitized world, data represents immense value. It is therefore important for companies from all industries to handle this data intelligently and draw the right conclusions from it. To achieve this, they often call on the help of experts: data scientists. This relatively new professional field is more in demand today than ever before, because data scientists know exactly how to process, organize and read data and how to derive forecasts from it.
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Data Scientist Definition: What is a Data Scientist?
Data scientists clean and analyze data, systematically evaluate it and extract valuable information from a huge amount of data.
Data scientists use the insights they gather to advise the management of their companies and thus help them to achieve strategically sensible goals more effectively. They can make forecasts or issue warnings (e.g. by analyzing all returns or complaints) and thus give their organization a major competitive advantage. Without this analysis and processing, companies are often left in the dark with their existing data volumes.
The demand for data scientists and the use of big data has therefore risen sharply in recent years. Data growth, and with it the ever-increasing need to track and analyze data volumes, is growing exponentially.
"In the past, companies only had analog locations on site. Human interactions were relevant there. Even if you just observe the guests, you can tell when they are lost or annoyed. Sales via a website or app is still a black box for many. (...) My job is to collect, structure and organize the data."
Data Scientist salary: What does a Data Scientist earn in Austria?
As in many other professions, the salary depends on various factors: the industry, the size of the organization as well as the experience you have gained and your own skills. Therefore, the salary increases continuously the more professional experience you have gained over the years.
Starting salary as a data scientist in Austria: Junior data scientist salary
Senior Data Scientist Salary
What does a data scientist do? Tasks and activities
Data scientists are constantly developing new analytical methods in their work in order to perfectly analyze the existing and extensive database and implement their requirements well. As large as the amount of data is, so is the information potential that the data scientist can extract. The available data is then linked and interpreted using various big data techniques.
In addition, a data scientist uses advanced analytics, a process for data processing that goes beyond the classic evaluation and visualization of data (business intelligence). This advanced analysis can also be used to make predictions about the future. With predictive analytics, data scientists can determine what effects certain changes (could) have.
This process turns big data into smart data.
Experts in data science are in demand to gain insights for management, who use these insights to make current and future business decisions. Their most important areas of responsibility include Big data, data engineering, data mining, smart data, machine learning and predictive analytics.
- Collection and evaluation of data from various relevant data sources
- Checking the data for accuracy, relevance and traceability
- Descriptive analysis of the collected data and connection to various databases (data warehouse or data lake)
- Presentation of own ideas and presentation of successful use cases
- Creation and validation of machine learning models
- Contact for domain experts for data science
Junior Data Scientist tasks
Collecting, cleansing and analyzing data and presenting results. As a Junior Data Scientist, these are also your tasks. At the start of your career, you may join a team of data scientists and provide support with requirements analysis, data preparation and presentation.
In order to make the step from Junior Data Scientist to Senior Data Scientist, it is advisable to familiarize yourself with the various areas of Data Science. A wealth of knowledge and additional strategic thinking will have a positive impact on your career path in this field.
Senior Data Scientist tasks
Becoming a data scientist - training, studies & further education
Due to the strong demand for data scientists, there are now various training opportunities to become a data scientist. The usual way to become a data scientist is through a suitable degree program. More and more universities are offering degree programs in data to meet the demand.
There is also the option of taking the path towards data science via certificate courses and further training.
Data science is a comparatively new field, which means that there is often not yet enough know-how in companies. Olga Kostova says: "Data science is so new that most people working in it are actually trained for something else. Universities only slowly started to offer specific programs for data science in 2016, at the same time as there was already demand from companies. This discrepancy is one reason why the know-how is not yet available in the companies themselves; there is a lack of human resources."
Data scientist training
There is no classic data scientist training or data scientist apprenticeship in Austria. In principle, a degree in data science, computer science or other relevant fields is required for this work.
There are numerous seminars and further training courses that can be taken online or in person to build up even more professional knowledge after graduation.
Another option for training as a data scientist is a six-month diploma course that provides in-depth training for working as a data scientist. This includes, for example, the "Data Engineering and Artificial Intelligence" course at Coders.Bay Vienna, where the costs are also covered by the Public Employment Service.
Data Scientist studies
A data science degree enables direct entry into a career as a data scientist. However, other university degrees, such as in physics, computer science, statistics or other STEM subjects, also provide a solid basis for familiarizing yourself with the subject area both theoretically and practically.
There are numerous universities in Austria that offer a Bachelor's or Master's degree program in Data Science. These include, for example, the Bachelor in Data Science at Modul University in Vienna, the Bachelor in Industrial Data Science at the University of Leoben and the Master's degree in Data Science at the University of Salzburg, to name just a few.
During your studies, you should ideally acquire skills and knowledge in the following areas or attend courses and lectures in these areas:
Data Management
Entrepreneurship
Information Design & Communication
IT
Data analytics
Data Scientist further training
Data Scientist lateral entry
Various online courses, seminars and further training courses offer a good starting point for both entry-level and lateral entry as a data scientist. Here, too, it is advisable to have previously completed a degree in an economics or IT subject. This is because most employers require a degree to fill this position.
Skills of a data scientist
Your technical skills as a data scientist are an important success factor for your future career. In addition to a strong understanding of mathematics and statistics, you should also have programming skills - especially in Python and R - and a basic (technical) understanding of software development and data analysis.
In addition, you should acquire knowledge of machine learning, data assimilation, business analytics or applied data science.
The most important hard skills of a data scientist are:
The most important hard skills of a data scientist are:
Extensive knowledge in the field of big data
Good math skills
Strong understanding of statistics
Programming skills, especially in Python and Java
Sound knowledge of SQL databases
Understanding of artificial intelligence and machine learning
Dealing with data management tools, such as Hadoop
In addition, as a data scientist, you should also stand out with your own soft skills, as you often come into contact with people in this profession.
The following soft skills therefore play an important role in your professional success:
Strong interest in new trends and technical developments in the field of big data, data science and business intelligence
Strong self-motivation, creativity and analytical skills
Ability to work in a team, intercultural knowledge and business fluency in English
Persuasiveness and stress resistance
Customer centricity via data analysis
Due to the very high demand, it is not always easy for companies to find qualified data scientists. We ask Olga Kostova what she advises companies that are urgently looking for data scientists:
"Companies need passionate product managers who put the customer at the center. You don't need a statistical model to understand that when your customer is in Europe, they want to see the prices online in euros, or that when they put two pillows and a blanket in a basket, they also need a couple of sheets. There is so much to be gained from pure logic and customer orientation. My recommendation: companies should first find people who understand the industry and the business, then ensure the data infrastructure (data collection, structure and quality), and finally train people to become data scientists."
Although data scientists are a great asset to a company, it is important to understand the customer first. Some of the things that data scientists find out after lengthy analysis could also be determined by product managers using pure logic.
Data Scientist Career: Opportunities on the job market as a data scientist
Your chances as a data scientist on the (Austrian) job market are extremely good. Hardly any other industry has seen such strong development over the last few decades as the field of data. The number of specialists in Austria can hardly keep up with this demand, which is why you have good prospects as a qualified data scientist with a degree.
For data scientist Olga Kostova, the trend is clear: "The need for data scientists is only going to grow. I see a growing demand for data scientists in the fields of medicine, mechanical engineering, agriculture, real estate and energy. This is in addition to the already traditionally high demand in IT, e-commerce and logistics."
If you are interested in a career in data science, now is the right time to find out more and look into the job profile of a data scientist. Because demand is not going to decrease for the time being.
Top vacancies for Data Scientist: Jobs throughout Austria
FAQ
A data scientist collects, cleans, extracts and analyzes data from which they can later draw conclusions. With these results, companies can make predictions and thus become even more competitive.
In Austria, you earn around €54,800 gross per year as a data scientist. Depending on your professional experience and organization, this salary can increase significantly.
For a career as a data scientist, a degree in data science or a STEM field is definitely advisable. In addition, further training and courses are available to deepen your knowledge.
Employers generally expect a degree for a position as a data scientist. So if you want to become a data scientist, a bachelor's degree in data science is a good idea.
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