Job profile
Data Scientist (m/f/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 sectors to handle this data intelligently and draw the right conclusions from it. This is where you come in as a data scientist. 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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Are you looking for an experienced Data Scientist (m/f/d)?
Does your company have large amounts of data at its disposal? Are you aware of the importance and informative value of relevant data in order to optimize your internal processes and align your current and future decisions accordingly? Qualified data scientists draw the right conclusions for your organization based on various analyses. Whether specialized professionals with years of experience in big data, data analytics or business analytics: with the help of our HR staff, you will find the right personnel for your vacancies.
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Data Scientist Definition: What is a Data Scientist?
Data scientists clean and analyze data, evaluate it systematically 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 strategic goals more effectively. They can make forecasts or issue warnings (e.g. by analysing all returns or complaints) and thus give their organization a major competitive advantage. Without this analysis and processing, the existing data volumes are often of little use to companies.
The demand for data scientists and the use of big data has therefore risen sharply in recent years. The growth in data and thus the ever-increasing need to track and evaluate data volumes is exponential.
Olga Kostova herself has been working as a data scientist freelancer for many years and describes her role as a data scientist as follows:
"In the past, companies only had analog locations on site. Human interactions were relevant there. Even if you just observe customers, you can tell when they are lost or annoyed.
Sales via a website or app is still a black box for many. However, unlike an analog site, you can manage thousands and even millions of users at the same time. My job is to collect, structure and organize the data."
Data Scientist salary: What does a Data Scientist earn in Germany?
On average, a Data Scientist in Germany earns a salary of €58,100 gross per year. The Hays IT Salary Report 2023 found that one in four data scientist salaries is higher than €86,500.
Senior Data Scientists can even expect to earn up to €130,000.
As in so many professions, the salary depends on various factors: the industry, the size of the company or organization and the experience and skills you have gained. Therefore, the salary increases continuously the more professional experience you have gained over the years.
Data Scientists earn the best salaries in Bavaria.
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Starting salary as a data scientist: Junior data scientist salary
Senior Data Scientist Salary
What does a data scientist do? Tasks and activities
A data scientist identifies and analyzes numerous structured and unstructured data sources and volumes.
He recognizes patterns, checks them and can make deductions from them, which he passes on to the responsible persons. His tasks also include tracking and monitoring the various data sources.
Data scientists are constantly developing new analytical methods to perfectly analyze the existing and extensive database. As large as the amount of data is, so is the information potential that the data scientist can extract. They then link the available data and interpret it using various big data techniques.
In addition, data scientists use advanced analytics, a data processing method that goes beyond the traditional 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 as a basis for making 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
The work of a Senior Data Scientist with several years of experience is often more project-based and strategic. In contrast to Junior Data Scientists, who take care of assigned tasks, their more experienced colleagues often oversee entire projects. They take care of the distribution of tasks and the time schedule. An important skill here is the correct prioritization of individual tasks in order to achieve good results.
Becoming a data scientist - training, studies & further education
Due to the strong demand for qualified data scientists, there are now various training options for acquiring the necessary skills in data science. The usual way to become a data scientist is through a suitable degree course. More and more universities are offering degree courses in data to meet the demand.
This is not always the case, as data science is a comparatively new field, which means that there is often not 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."
There is also the option of taking the path towards data science via certificate courses and further training.
Data Scientist training
There is no classic data scientist training program in Germany. Generally, a degree in data science, computer science or other relevant fields is required to work in this field.
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.
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 Germany that offer a Bachelor's or Master's degree course in Data Science. These include, for example, TU Aschaffenburg (Bachelor), Kiel University of Applied Sciences (Master) and Darmstadt University of Applied Sciences (Bachelor), 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
KNOWLEDGE IS POWER
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 a Master's program, you should acquire knowledge specifically in Machine Learning, Data Assimilation, Business Analytics or Applied Data Science.
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 in order to fill the various roles and meet the different and growing demands.
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 before 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 urgently need 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 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 discover after lengthy analysis could also be determined using pure logic.
Data scientist career: opportunities on the job market as a data scientist
Your chances as a data scientist on the job market are extremely good. Hardly any other industry has seen such strong development over the last few decades as the field of data.
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: data scientist Jobs (m/f/d)
FAQ
A data scientist collects, cleanses, extracts and analyzes data using modern methods such as data mining and machine learning. Companies can then use these results to make predictions and thus become even more competitive.
As a data scientist in Germany, you earn an average gross salary of € 58,100 per year. Depending on your professional experience and organization, this salary can rise sharply to as much as €130,000.
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.
