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Data Scientist (m/f/d)
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Definition of a Data Scientist (m/f/d): What is a Data Scientist (m/f/d)?
Data Scientists systematically clean, analyze, and evaluate data to extract valuable insights from vast amounts of information. With these insights, they advise their company’s management, helping to achieve relevant strategic goals more effectively. They can make forecasts or issue warnings (e.g., by analyzing feedback or complaints), providing a significant competitive advantage to their organization. Without this analysis and processing, the available data would often be of little use to companies.
The demand for Data Scientists and the use of big data have significantly increased in recent years. The growth of data and the ability to track and evaluate it are developing exponentially.
Olga Kostova, an independent Data Scientist for many years, describes the high demand for data scientists:
“In the past, companies only had analog sites on-site. Human interactions were relevant. By observing customers, you could notice if they were lost or angry. Selling via a website or an app remains a black box for many. But you can handle thousands, even millions of users at the same time, unlike an analog site. My role is to collect, structure, and classify data.”
Data Scientist (m/f/d) Salary in Switzerland: How Much Can You Earn?
In Switzerland, the average salary for a Data Scientist is around CHF 96’000.00 gross per year. Generally, salaries range between CHF 72’000.00 and CHF 170’000.00 per year, depending on several factors such as the industry, company size, experience, and acquired skills. The more experience you accumulate, the higher your salary.
The cantons of Uri and Neuchâtel offer the best salaries for Data Scientists, with the insurance sector leading in remuneration.
Starting Salary for a Junior Data Scientist (m/f/d) in Switzerland
Senior Data Scientist Salary
What Does a Data Scientist (m/f/d) Do? Tasks and Activities
A Data Scientist analyzes and identifies various data sources, whether structured or unstructured. They detect patterns, validate them, and draw conclusions to share with stakeholders. Continuous monitoring of data sources is also part of their responsibilities.
Data Scientists constantly innovate by developing new analytical methods to make the best use of the vast databases available. The quality of the information they can extract is as crucial as the quantity of data. They connect and interpret data using advanced Big Data techniques.
By using advanced analytics, a Data Scientist goes beyond traditional analysis and visualization (business intelligence). This approach allows for future predictions through predictive analysis, determining the potential impact of certain changes.
This process transforms Big Data into Smart Data.
Data science experts provide valuable insights to management for current and future business decisions. Their main areas of activity include Big Data, Data Engineering, Data Mining, Smart Data, Machine Learning, and Predictive Analytics.
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- Collecting and analyzing data from various sources
- Verifying the accuracy, relevance, and traceability of data
- Descriptive data analysis and connection to databases (Data Warehouse or Data Lake)
- Presenting ideas and successful use cases
- Creating and validating machine learning models
- Acting as a contact for domain experts in data science
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Junior Data Scientist (m/f/d) Responsibilities
As a junior Data Scientist, your main responsibilities include data collection, cleaning, analysis, and presenting results. You will often work within a team of Data Scientists, contributing to needs analysis, data preparation, and result presentation. To advance to a senior Data Scientist position, it is recommended to familiarize yourself with various data science domains. Broad knowledge and strategic thinking are major assets for progressing in this field.
Senior Data Scientist (m/f/d) Tasks
With several years of experience, a senior Data Scientist focuses more on strategic projects. Unlike juniors who perform assigned tasks, seniors often manage entire projects, distributing tasks and planning their execution. A key skill is the ability to prioritize tasks correctly to achieve optimal results.
Becoming a Data Scientist (m/f/d): Education, Studies, and Continuous Training
Given the growing demand for qualified Data Scientists, various training options are available to acquire the necessary skills in data science. The traditional path involves appropriate higher education, with more and more institutions offering specialized data science programs. It is also possible to train through certifications and continuous education.
Since data science is a relatively new field, many companies still lack expertise in this area. Olga Kostova explains: “Data science is so new that most people interested in it are actually trained for something else. It was only in 2016 that universities slowly began offering specific programs for data science, while the demand from companies already existed. This gap is one of the reasons why expertise cannot yet exist within companies themselves, as human resources are lacking.”
Data Scientist (m/f/d) Training
In Switzerland, there is no traditional training to become a Data Scientist. Generally, it is necessary to have completed studies in data science, computer science, or relevant fields. To deepen your knowledge after your studies, numerous seminars and continuing education courses are available online or in person.
Data Scientist (m/f/d) Studies
Studies in data science directly pave the way for a career as a Data Scientist. Other university degrees, such as those in physics, computer science, statistics, or other STEM disciplines, also provide a solid foundation for this field. In Switzerland, several universities offer bachelor’s or master’s programs in data science, such as FHNW (bachelor), Fachhochschule Graubünden (master), and ZHAW School of Engineering (bachelor).
During your studies, it is recommended to acquire skills in the following areas:
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- Data Management
- Entrepreneurship
- Information Design and Communication
- IT
- Data Analysis
Continuing Education for Data Scientists (m/f/d)
With the growing popularity of this field, more and more continuing education options for Data Scientists are available. Various institutes offer online seminars or in-person training in data science and big data, often accompanied by a certificate. These continuing education courses are particularly effective when combined with a university degree.
Can You Become a Data Analyst (m/f/d) Without a Degree?
DATA SCIENTIST (m/f/d) SKILLS
The professional skills of a Data Scientist are essential for success in this field. In addition to a solid understanding of mathematics and statistics, programming skills, particularly in Python and R, as well as technical knowledge in software development and data analysis, are crucial. A master’s degree in Machine Learning, Data Assimilation, Business Analytics, or Applied Data Science is also recommended.
Hard Skills of a Data Scientist (m/f/d):
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- Extensive knowledge of Big Data
- Strong mathematical skills
- Deep understanding of statistics
- Programming skills, especially in Python and Java
- In-depth knowledge of SQL databases
- Understanding of artificial intelligence and Machine Learning
- Use of data management tools, such as Hadoop
In addition to technical skills, soft skills are essential to meet the diverse demands of the job:
Soft Skills of a Data Scientist (m/f/d):
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- Interest in new trends and technical developments in Big Data, Data Science, and Business Intelligence
- Strong personal motivation, creativity, and analytical capabilities
- Ability to work in a team, intercultural knowledge, and proficiency in English for negotiations
- Persuasive ability and stress resistance
PRIORITIZING THE CUSTOMER BEFORE DATA ANALYSIS
Due to high demand, it is often challenging for companies to find qualified Data Scientists. Olga Kostova advises companies to focus on the customer first: “Companies need passionate product managers who put the customer at the center of their concerns. They don’t need a statistical model to understand that their customer, when in Europe, wants to see prices in euros or that when they put two pillows and a blanket in a cart, they also need some sheets. There is so much to gain with pure logic and customer orientation. My recommendation: companies should first find people who understand the sector and the business, then ensure the data infrastructure (data collection, structure, and quality), and finally train people to become Data Scientists.”
While Data Scientists are a major asset for a company, it is crucial to understand the customer first. Many discoveries made by Data Scientists after long analysis could be observed through simple logic.
DATA SCIENTIST (m/f/d) CAREER: JOB MARKET OPPORTUNITIES
Career prospects for Data Scientists are extremely promising. Few sectors have experienced as rapid development as data in recent decades. According to Olga Kostova, “The need for Data Scientists will only grow. I see increasing demand for Data Scientists in medicine, engineering, agriculture, real estate, and energy, in addition to the already high demand in IT, e-commerce, and logistics.”
If you are interested in a career in data science, now is the perfect time to explore the Data Scientist job profile, as the demand is not going to decrease anytime soon.
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Top vacancies for Data Scientist (m/f/d): Jobs throughout Switzerland
faq
A Data Scientist collects, cleans, extracts, and analyzes data to draw conclusions. These analyses enable companies to make forecasts and improve their competitiveness.
In Switzerland, a Data Scientist earns an average of around 96,000 CHF gross per year. This salary can significantly increase depending on experience and the organization.
To become a Data Scientist, it is highly recommended to have a degree in data science or a STEM field. Continuing education and specialized courses also help to deepen skills.
Generally, employers require a university degree for a Data Scientist position. A Bachelor’s in Data Science is therefore a valuable asset for entering this career.
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