Amid rising demand for data experts, the average data scientist and data analyst salary is also steadily growing. While this is true around the world, Germany, one of Europe’s tech hubs, is no exception.
If you’ve been bitten by the data bug and are a resident of Germany, you might be wondering: Should I become a data analyst or a data scientist?
While both roles are proving vital to the German economy, it’s worth considering the differences between them, including which offers the most competitive salary.
In this comprehensive guide, we dive into the intricacies of these two data-focused roles, providing a side-by-side comparison of their responsibilities. We’ll also explore the latest salary trends and the factors influencing them to answer the question: Data analyst vs data scientist salary in Germany, which is higher?
- Data analyst vs data scientist: What’s the difference?
- Salary trends and factors influencing analyst and data scientist salary in Germany
- Salary comparison: Data analyst vs data scientist in Germany
- Factors influencing salary differences
- Career outlook and growth opportunities
- How to become a data analyst or scientist in Germany in 2023
Ready? Then with no further fuss, let’s jump in!
1. Data analyst vs data scientist: What’s the difference?
There are many roles within the data industry, but two quintessential ones are data analysts and data scientists. In this section, we explore these distinct but interconnected professions, what each does, and the impact they typically have on a business.
Data analysts: Unlocking insights from past data
Data analysts are skilled investigators. Their primary focus is examining historical data, uncovering insights and patterns to inform future decision-making.
The data analyst’s role typically involves gathering, cleaning, and organizing data from a variety of sources, including databases, spreadsheets, and other repositories. They’ll apply statistical techniques and visualization tools (among other processes) to transform raw data into meaningful, easily understood insights, dashboards, and reports.
So what value do data analysts offer? In short, they help organizations understand their past performance (for example, by analyzing sales figures) or identify existing, past, and future trends based on what has happened in the past.
In practical terms, their work is broad; they might uncover insights into customer behavior or evaluate the effectiveness of a particular business operation. Essentially, they’re business intelligence experts who help stakeholders make better-informed decisions.
Data scientist: Innovative applications and longer-term strategy
While data scientists share many skills with data analysts, their role is typically more senior.
And although they may explore data the way data analysts do, their focus is usually on finding novel ways to innovate using data. For example, they might devise applications that utilize natural language processing, image recognition, fraud detection, and more.
The data scientist role typically involves more complex techniques than data analysts. They’ll regularly use machine learning and AI algorithms, and work with far more complex datasets and associated tools, such as distributed computing software. Data scientists are typically expert coders, too, using various programming languages, and they’ll have a much deeper understanding of statistics and other computational methods.
Within most businesses, data scientists may not be involved in day-to-day decision-making like data analysts are. Instead, they add value by building and fine-tuning sophisticated models that transform how a business operates. Their work is usually linked to long-term strategy, for instance, expanding into new markets or optimizing production processes.
Although we’ve outlined the differences here, it’s worth noting that there’s also plenty of crossover between data analytics and data science, too. You can learn more about it in this guide: Data Analytics vs Data Science: What’s the Difference?
2. Salary trends and factors influencing analyst and data scientist salary in Germany
As mentioned, data professionals in Germany—including data analysts and data scientists—are in high demand.
This is evidenced by the fact that a data scientist’s salary in Germany is typically higher than many other professions.
Two key factors contributing to the higher earning potential for data scientists are their specialized skillset and focus on advanced innovation. However, a data analyst’s salary in Germany also remains competitive, reflecting their crucial role in day-to-day business operations.
Other factors influencing salary levels for these two roles include:
- years of experience
- educational background
- industry specialization
It’s also worth considering that data scientist salaries in Germany will differ depending on geography. In regions with higher demand, for example, in cities like Berlin and Frankfurt, where the tech sectors are booming, pay for data jobs is often much more lucrative.
Finally, your level of proficiency with in-demand programming languages, such as Python or R, and expertise in cutting-edge machine learning and AI technologies can further enhance your earning potential. Of course, things like job satisfaction, career progression opportunities, and simply the joy of living overseas can also be important considerations.
It’s not all about how much you earn—but it helps!
3. Salary comparison: Data Analyst vs. Data Scientist in Germany
So, down to the nitty-gritty. How much can data analysts and data scientists earn in Germany? Although a precise figure can be hard to pin down, we can get a reasonable estimate by exploring tracked salary data from popular comparison sites such as Indeed, salary.com, and Glassdoor.
For this post, we’ve used data from Salary Expert. After comparing salaries in Germany across numerous sites, we found that Salary Expert offers estimates falling roughly in the median range. They also use data from the Economic Research Institute, which, over many years, has collated salary data from over 1,000 industries and in 10,000+ global locations.
According to Salary Expert, the median data analyst salary in Germany is €90,827 (approximately $99,000 USD), while the average data scientist salary in Germany is €109,951 (approximately $119,800 USD). As you can see, both roles have high earning potential, although data scientists earn more than data analysts for reasons outlined in the next section.
Bear in mind that salary estimates fluctuate depending on the economic situation, so ensure you click the links provided to see the most up-to-date estimates.
4. Factors influencing salary differences
So, we’ve established that data scientist salaries in Germany tend to be higher than those for data analysts. But why?
The difference between data analyst and data scientist salaries in Germany is affected by each role’s respective skill set and impact. Let’s take a look:
Skill complexity: While both are skilled roles, data scientists require more advanced expertise in statistical techniques, machine learning, and AI. In addition, their ability to work with large, unstructured datasets and their superior proficiency using languages like Python or R explains why they command higher salaries than data analysts.
Job responsibilities: Data analysts primarily examine historical data to aid day-to-day decision-making. Meanwhile, data scientists must conduct deeper exploration and carry out complex predictive modeling to inform longer-term strategies. This added responsibility means they can command higher salaries.
Impact: With their broader responsibilities and higher-level skillset, data scientists drive longer-term growth by revolutionizing business operations (at least on paper!) While data analysts also play a crucial role, their impact may be perceived as less influential, meaning they might struggle to earn as much.
Demand and supply: Being a more senior role, and requiring more experience means data scientists are in higher demand. In turn, this leads to higher salaries. While data analysts are equally invaluable, because their skills are usually more abundant, there is less intense demand and, subsequently, lower salaries.
Industry: As a data professional, your salary will always vary between jobs and industries. In the technology and finance sectors, however, which are at the bleeding edge of innovation, these roles typically command higher pay. But because of their innovative nature, these sectors also usually seek out more specialized data scientists. Many data analysts find it easier to come by a less well-remunerated job in a less competitive sector.
All this said, while data scientists typically earn more, as businesses continue to recognize the importance of data-driven working, the salary trends for both roles are likely to remain competitive compared to other professions.
5. Career outlook and growth opportunities
Fortunately, the career outlook for data analysts and data scientists in Germany looks promising, with more and more businesses hiring for these roles.
This is particularly true in tech hubs such as the capital, Berlin, and cities like Frankfurt, the largest financial hub in continental Europe. Data professionals will find many opportunities available in industries ranging from fintech to healthcare, marketing, and more.
Meanwhile, with the advent of artificial intelligence products—from smart assistants to recommendation engines and generative AI—data scientists are proving vital to their further development. Data experts are also playing an increasingly prominent role in the deployment of AI ethics guidelines and guardrails.
While the truth is that we don’t yet know how these roles will evolve, what is clear is that the demand for data professionals (data analysts and data scientists among them) will continue to rise in Germany and elsewhere.
Many traditional jobs are at risk due to the emergence of these new technologies, but the very same boom is leading to a greater need for higher-level technical, digital, and data skills, making these future-proofed professions excellent ones to move into.
To learn more about your career as a data expert might progress, check out this guide: What is the typical data analyst career path?
6. How to become a data analyst or scientist in Germany in 2023
Seen enough? Ready to take the plunge? Good for you!
Whether you’re already living in Germany and are interested in becoming a data analyst or data scientist, or are planning to relocate here, let’s look at some specific considerations as you start on your journey.
Get the right skills
Before getting started, you’ll need a relevant qualification or certification in data science, computer science, statistics, or a related field.
Many data analysts and data scientists hold a bachelor’s or master’s degree. Recently even more of them have a qualification from a dedicated data bootcamp or career-change program. Germany is particularly well-service for this. There’s a whole range of data bootcamps in Berlin alone, many of which you might be able to take for free with the help of the German government.
Alternatively, consider specialized courses in programming languages (e.g., Python, R), statistical methods, machine learning, and data visualization. Platforms like Coursera, Udemy, and edX offer various data science certifications, as well as providers like CareerFoundry offering ML with Python and data viz specializations.
Gain practical experience
Practical experience is essential in data science. Seek out data internships in Germany to gain real-world experience.
You could also carry out personal data-related projects and build a portfolio to show off your skills. Need some inspiration? Check out this article: 9 project ideas for your data analytics portfolio
Network with the data community
Networking helps you stay updated on the latest techniques and job opportunities. It can also connect you with more experienced professionals. Keep them sweet, and they may offer free guidance!
While English is widely used in the tech industry, particularly in big cities, learning German will still help you integrate into the local work environment.
It can also open up a lot more additional job opportunities in cases where German language skills are a requirement, putting you ahead of a lot of the international competition.
Develop and use job search strategies
Use popular German job search and networking platforms such as Xing, StepStone, or the ever-ubiquitous LinkedIn! Here you will find data analyst and data scientist positions in your region. When applying for jobs, tailor your resume and cover letter to highlight relevant skills and experiences for each application.
Apply for a Bildungsgutschein (education voucher)
If you’re currently a German resident, are unemployed, and registered with the German employment agency (Agentur für Arbeit), you may be eligible to apply for a Bildungsgutschein. This voucher can help cover the costs of training and education programs, including data science courses, improving your chances of finding employment.
Learn more: How to study data with a Bildungsgutschein
The main thing is to be proactive, dedicate yourself to lifelong learning, and persist in finding the right opportunities. While language skills, a strong skillset, and an understanding of the German job market will help, the thriving data landscape in Germany will remove many barriers to finding an exciting new challenge that pays well.
To dig deeper into how to land a data job, check out: How to become a data scientist
So there we have it!
In this post, we posed the question: data analyst vs data scientist salary in Germany, which is higher? The answer: data scientist salaries! Nevertheless, both can enjoy rewarding careers with promising salary prospects compared to the national average income.
The main thing is to follow your passion, equip yourself with the right skills, and stay updated with the latest trends in the field. Whether you choose to unveil the mysteries of data as an analyst or create groundbreaking AI solutions as a data scientist, your expertise will be valued and well-compensated.
If you’re considering a career in either role, start by acquiring a relevant qualification or certification. Then, gain some practical experience, and network with your local data science community to support your job search. Learning German can also be beneficial (although not mandatory) and if you’re retraining, check out if you’re eligible for Germany’s unique training voucher, the Bildungsgutschein.
Beyond these tips, do some further research, but most of all: enjoy yourself! While the journey can pose a challenge, it should also be fun!
To learn more about data, why not enroll in CareerFoundry’s free 5-day data short course? Alternatively, check out the following beginner’s guides: