Did you know that Facebook has around 2.9 billion active monthly users? As reported by Statista, Meta owns four of the largest social media platforms; Facebook, WhatsApp, Messenger, and Instagram, each of which has about one billion active monthly users. The data generated from these apps are huge and require professional expertise to conduct analysis and market the companies to more people.
With the focus on data increasing every day along with huge data volumes, the world requires skilled professionals to analyse them and draw meaningful information that can be used to drive businesses forward. Data science as a career path has been receiving huge attention worldwide due to its scope and numerous career opportunities. Data scientist, data analyst, statistician, business analyst, data engineer, and data architect are some of the career pathways open to data science graduates.
If you are a data science enthusiast, discover more about the career opportunities in the field of data science below.
What is Data Science?
Data science is an interdisciplinary field that studies large amounts of raw data to extract meaningful insights and patterns from it. Data scientists use various programming languages, statistical methods, machine learning techniques, and advanced computer science to analyse data and derive information.
The insights obtained from data analysis can be used to guide decision-making, improve security measures and efficiency, implement targeted marketing strategies, and drive business growth.
What is a career pathway in data science?
A data science career path involves a structured journey from foundational skills such as programming languages, database construction and entry-level work to advanced roles like Data Scientist and Data Engineer with specialisations in machine learning or data architecture. Over time, this can lead to leadership roles such as Chief Data Officer or Chief Technology Officer.
What are the career opportunities with data science?
The U.S. Bureau of Labor Statistics predicts a 36% growth in data scientist jobs from 2021 to 2031. As companies are driven by digital technologies and the internet, there is an increased dependence on data science professionals to grow their businesses. Almost every industry in the world has become reliant on data science professionals as the digital revolution has set in. Healthcare, finance, hospitality, education, banking, retail, real estate, and telecommunication are some of the popular industries in demand for data scientists and analysts.
As a result, a career in data science opens up many pathways in industries all over the world. No matter what your specialisation, there is likely to be a perfect data science job for you.
Here are just some of the career opportunities in data science:
Data administrator
Data administrators monitor, maintain and manage their organisation’s data, helping to control data assets and using different applications to ensure that data is processed correctly.
Data engineer
Data engineers create the architecture that stores a company’s data. In addition to determining how the company captures and stores data, data engineers design warehousing solutions and perform data modelling duties.
Data scientist
Data scientists extract raw data from a variety of sources using a range of tools including artificial intelligence and machine learning, which they then interpret into relevant information. They then present this information in an accessible way such as through reports and presentations.
Data analyst
Following data-gathering exercises and interpretation, data analysts use data to identify how an organisation can be more efficient via automation. They also track the organisation’s key performance indicators to determine how the business is performing overall.
- Data architect
Data architects are responsible for developing a data strategy for the organisation. You must design the overall data infrastructure which includes data models and procedures and manage the data flow. You should oversee the entire lifecycle of a data operation and collaborate with other data science professionals to meet the company’s requirements.
PayScale reports the average annual salary of a data architect to be €75,121 which is much more than other data science jobs.
Entry-level data science roles to start your career
An entry-level data science role is a great way to get started in the industry, and can ultimately lead to advanced roles with high-paying salaries.
Entry-level data science roles involve assisting senior data scientists, organising raw datasets, running simple, supervised models and analysis and creating reports and presentations that make the data easier to understand.
These entry-level roles allow you to build a strong foundation in the data science industry while also showcasing your skills, and are the first step towards more advanced roles in the future.
The average starting salary for an entry-level data science role can vary based on location, role type and industry. The starting salary for a junior data scientist in Germany is around €48,000 a year.
Career progression in data science
A degree in data science opens up many career paths in industries all over the world.
During your degree, you’ll learn relevant skills and gain hands-on experience so that you will be prepared to enter the data science industry after graduation.
Your salary and job opportunities increase as you gain more experience in the field, and you can succeed by continually refining your skills and seeking out new knowledge. With enough experience in entry-level positions, you’ll be able to progress to more advanced roles with higher salaries and could eventually be qualified for leadership positions such as Chief Technology Officer.
Popular career pathways in data science by specialisation
A master’s degree in data science can open up a wide range of exciting career opportunities.
Data science roles can vary based on your specialisation. Some prefer more business-oriented roles such as market research analyst and data scientist, while others specialise in more technical fields, such as machine learning and data engineering. These specialisations offer unique pathways.
For example, a common career pathway for machine learning engineers involves starting as a junior machine learning engineer, advancing to a senior role before finally becoming an AI specialist.
For data engineers, the common pathway is as follows: Data Engineer → Senior Data Engineer → Data Architect.
The common pathway for market research analyst is as follows: Market Research Analyst → Senior Analyst → Market Research Manager → Market Strategy Consultant.
For data scientists, the common pathway is as follows: Junior Data Scientist → Data Scientist → Senior Data Scientist → Lead Data Scientist → Chief Data Scientist.
Ultimately, a career in data science offers many fantastic opportunities for advancement no matter your specialisation.
Key skills to start a career in data science
Data science is a competitive industry, and being successful requires a range of hard and soft skills.
The following are essential skills that you should have before entering the field of data science.
Programming
Knowledge of programming languages is essential for sorting and analysing large amounts of data.
Python is the most popular programming language, while others include R, SAS and SQL.
Data wrangling
In order for complex data sets to be analysed, they must first be cleaned and organised via data wrangling. This involves categorising data by patterns and trends and correcting any input data values.
Cloud computing
Familiarity with cloud computing services such as Amazon Web Services, Microsoft Azure and Google Cloud is essential for analysing and visualising data stored in cloud platforms.
Data visualisation
Data visualisation is a key skill for data scientists, as it helps them analyse and categorise data before presenting it in an accessible and compelling format, such as charts and graphs.
Interpersonal skills
Soft skills such as communication and collaboration are essential in data science. Building strong interpersonal skills will help you work closely with your colleagues and present data to stakeholders.
Tips for getting started in data science careers
No matter which industry you want to enter, there are some tips that can help you get started on a career path in data science. Educating yourself on the various nuances of data science, earning certifications, gaining practical experience, and building connections are the ways to kickstart a career in data science.
You can get into entry-level jobs in the sector with a bachelor’s degree in mathematics, computer science, or statistics. But it is better to pursue a master’s in data science to grab more exciting and well-paying opportunities as the competition is as high as the demand for data science jobs.
Additionally, you can also enrol in certification programmes to develop specific skills that are relevant to particular data science career pathways. There are plenty of certification programmes that deal with industries such as logistics, banking, finance, healthcare, and business. Choose a programme that interests you and build your skills and portfolio to catch the employer’s attention.
You can also work as an intern during your study programme or soon after to add up the experience in your resume. This way, you can network with like-minded people and also gain some valuable experience that will help your data scientist career growth, taking you one step closer to your dream career.
Career opportunities in data science for international students in Germany
After completing your master’s degree in data science, you’ll have everything you need to build your career in Germany.
International students are able to stay in Germany for some time following graduation, so you’ll be able to begin the search for your dream career in earnest.
Germany is home to numerous national and multi-national companies, with data scientists being highly sought after in many industries.
Depending on your skill set, specialisation and experience, you could earn up to €130,000 a year as a data scientist in Germany.
How to start your career in data science
Educating yourself on the various nuances of data science, earning certifications, gaining practical experience, and building connections are the ways to kickstart a career in data science.
You can get into entry-level jobs in the sector with a bachelor’s degree in mathematics, computer science, or statistics. But it is better to pursue a master’s in data science to grab more exciting and well-paying opportunities as the competition is as high as the demand for data science jobs.
Additionally, you can also enrol in certification programmes to develop specific skills that are relevant to particular industries. There are plenty of certification programmes that deal with industries such as logistics, banking, finance, healthcare, and business. Choose a programme that interests you and build your skills and portfolio to catch the employer’s attention.
You can also work as an intern during your study programme or soon after to add up the experience in your resume. This way, you can network with like-minded people and also gain some valuable experience that will take you one step closer to your dream career.
If you are ready to build your data science skills, join the MSc Data Science programme offered at the University of Europe for Applied Science (UE), Germany and get started. The programme covers important topics in data science such as data analytics, machine learning, predictive modelling, deep learning, cloud computing, and data engineering.
During the programme, you will develop theoretical and practical knowledge of all essential data science concepts which will set you apart in the competitive job market. You also have the opportunity to choose an interdisciplinary elective out of game design, digital media communication, or UX/UI design which will give you an added advantage in your job search.