"Turning Data into Success!" That is how the job description of a data scientists sounds like. Very lucrative one. Back in 2012, an eternity by digital standards, the Harvard Business Review dubbed the profession of data scientist "The Sexiest Job of the 21st Century". Today, a decade later, the prophecy has become reality. Want a little proof? In 2020, the amount of digital data generated and replicated worldwide was 64.2 zettabytes. In 2025, it is predicted to be over 181 zettabytes worldwide. An increase that is as gigantic as it is rapid.
But what makes the work of data scientists so sexy? And how can IT career changers get a piece of the big, lucrative "data pie"?
Hot, Hotter, Big Data
In Silicon Valley, the masters of numbers, the rulers of the confusing, unstructured mountains of data, are considered the rock stars of the industry. Lucrative pay, oversized bonuses, extra wishes and individual "star" attitudes: all part of the deal between companies and data scientists. At least in the USA. Hardly anyone asks for less than 100,000 euros in annual salary. The European market is also following suit. The competition for the best IT talent has long been international. IT career changers, listen up! This also applies to people who have little or no job experience. Why? It's simple. Extreme demand has been outstripping supply for years. This drives up the salaries and egos of Data Scientists alike. What's more, data is now part of the core business of nearly every industry. From banking to insurance, e-commerce to medicine, everyone lives off customer data. And this will not change in the future: The global data volume is currently doubling every two years. So how can career changers - trained scientists, economists or engineers - get a juicy slice of the big, very big "data pie"? Super easy. Just register.. and dive into our neue fische Data Science Bootcamp for 12 weeks. After that? You'll be a rock star! 💥
What do Data Scientists do? - a job desciption
Data Scientists work with a wide variety of data and put it in relation to each other according to specifications. This means that they have a huge amount of unstructured raw data in front of them, which they have to structure. This is followed by analysis and the derivation of business decisions and development forecasts. Number crunchers recognize recurring patterns from the past (pattern recognition), which can be decisive for business success. The decisive factor is not who generates the most data from users, but who can make sense of this data. The job description in a nutshell: Data Scientists turn Big Data into Smart Data!
The job sometimes also includes implementing tracking and constantly monitoring data. Often, data scientists develop their own analytical methods for better analysis. But what it all boils down to is predicting developments and making recommendations for action. This is what every management depends on.
Tasks at a glance:
Data Management, Mining and Analysis (Advanced Analytics)
Formulation of a relevant business issue
Collection of required data
Identification and development of data-based use cases
Identification of suitable (Big Data) data sources
Connection of data sources or access to data warehouse or data lake
Examination of data quality
Creation of attributes (feature engineering)
Training, testing and validation of machine learning models ("Big Data Analytics")
Interpretation of results, operationalization of findings and ML models
What skills are required?
Logically, the basis of everything should be a passion for math, statistics as well as stochastics. Nerdy numerical reasoning can be gold plated. After all, nothing works without a strong background in this area. Furthermore, Data Scientists should be familiar with Deep Learning and Machine Learning and have mastered the basics of software development, including common programming languages such as Python and R. The job description makes clear that some hard skills are a mandatory entry requirement here. However, there is nothing that cannot be learned. Also for career changers in a super turbo fast, 12-week bootcamp. In the bootcamp you will learn to use tools like SQL and Pandas to extract and manipulate data from various sources. After data manipulation, we move on to Exploratory Data Analysis. In addition, we will dive into the world of machine learning and neural networks together.
Skills of Data Scientists:
Mathematical and statistical know-how
Basics in Deep Learning and Machine Learning
Programming languages such as Python and R
Experience in working with AI applications
Business thinking and business acumen in controlling, marketing and finance
Correct, very accurate work
Proactive problem solving
Critical, logical thinking
By now at the latest, it should be clear why Data Scientist*s can afford to have rock star attitudes. Or?
What does a Data Scientist earn?
If you know a lot, you can get paid well - especially if your knowledge is in high demand. Career starters who have programming skills and a basic knowledge of artificial intelligence, machine learning and initial practical experience start with a salary of around €50,000 per year. As a mid-level Data Scientist, the salary range is €60,000 and up to around €80,000 annually. The rest... open end. Anything is possible in this field. The balance of power is clearly on the side of the knowledge carriers.
The job description got you hooked? Become a knowledge bearer! Secure the rock star hype!
In the medium to long term, the balance of power will continue to shift in favor of data scientists. So: Cram for 12 weeks and then dig for data gold. What more do you want? Nothing? Okay, then go for it... Register for the Data Science Bootcamp!🌈