Prof. Dr. Michael Schneider
Prof. Dr. Michael Schneider has headed the German Post Chair for Optimization of Distribution Networks (DPOR) at RWTH Aachen University since June 2016.
M.Sc. Data Analytics & Decision Science
Transform data into value and tackle managerial challenges - with a Data Management Master´s Degree!
Master of ScienceBecome a Data Expert for Business and Management
Learn how to generate true value from data and enhance your professional profile with essential management skills. Deep dive into the exciting worlds of Operations Research, Artificial Intelligence and Big Data. By knowing how to apply the right set of methods from the fields of Data Analytics and Decision Science to any situation, you will become a real problem solver. Be it as a coding superstar, a mediator between tech and management, or even in a leadership position, with this Data Managment Master´s Degree, nothing will be stopping you from building your career.
OVERVIEWData Management Master for Young Professionals
Our unique master’s program M.Sc. Data Analytics & Decision Science makes you a data specialist.
Language | English |
|---|---|
Scope | 4 semesters, 120 CP |
Format | Full-time, on campus in Aachen, Germany |
Degree | Master of Science, RWTH Aachen University |
Study Start | October 01, 2025 |
Costs | 30.000 EUR (Early Bird: 27.000 EUR) |
Next Application Deadline | Early Bird: January 15, 2025 |
Career OptionsData Is Everywhere: Job Fields
Discover possible job fields you can open up with this degree.
Course ContentModules and Topics
Refresh your previous expertise and acquire core knowledge in the relevant methodological domains of Data Analytics and Optimization within the first semester. This lays the foundation for successful studies. You will build up fundamental core knowledge in fields of Machine Learning, Heuristic Optimization or Predictive Modelling.
In this practice-oriented module, you will go through an entire analytics project and learn how to apply your theoretical knowledge to an actual optimization problem. After identifying the individual business needs, you apply machine learning methods and operations research techniques to collect, evaluate, and analyze data to make accurate predictions and well-founded decisions. At the end of the module, you will present your solution to business representatives and directly receive valuable feedback.
In addition to providing you with the necessary theoretical knowledge and data-driven techniques and methods to succeed in a digitized economy, the program also offers detailed insights into the most popular application areas: Marketing, Finance, Sustainability and Healthcare.
Two Soft Skill modules will fine-tune your professional appearance and behavior, setting you up for optimal performance in the business world after completing your studies. Moreover, in the last semester, two General Management modules will prepare you to re-enter the professional world and equip you with managerial basics, tailored especially for technical professions.
During an internship, you apply your skills and gain hands-on work experience in an industry work placement at a medium-sized or global enterprises such as Deutsche Post DHL, BMW, Bosch, and others. You acquire knowledge about technical materials and processes used in current practice as well as corresponding economic considerations and procedures. Equally important are the insights into social processes and structures in the companies.
By writing a master's thesis at the end of the program, you will demonstrate your ability to solve a methodological or analytic challenge using the knowledge acquired during the program and scientific research methods.
Course ContentCurriculum
No dusty theory, but hands-on education
Our core competency is to teach you in a method-based way to make you an industry-independent data expert. At the same time, we put a lot of emphasis on practice-oriented modules and deal with real case studies from various business partners of our ecosystem. An internship additionally secures the well-balanced mix of theory and practice as part of the curriculum. Various elective modules will give you the opportunity to specialize in both the technological and business aspects to be best prepared for your dream job. The curriculum is created in partnership with the renowned professors from the Faculty of Business and Economics at RWTH Aachen University, and is enriched by insights from leading business and industry experts.
4 SEMESTERS120 CP
Compulsory Courses | 30 CP
- Statistics & Mathematics
- Algorithms & Data Structures
- Machine Learning
- Predictive Modeling
- Optimization Models
- Design & Analysis of Algorithms
Compulsory Courses | 15 CP
- Strategic Negotiations
- Analytics Project
Application Areas (3 out of 4) | 15 CP
- Marketing Analytics
- Financial Analytics
- Health Care Analytics & Management
- Energy & Climate Analytics
Compulsory Courses | 15 CP
- Heuristic Optimization
- Advanced Machine Learning
- Scientific Work & Presentation
Internship | 15 CP
Compulsory Courses | 10 CP
- Management & Technology Perspectives
- Logistic Systems Management
Master Thesis | 20 CP
ElectivesData Management Application Areas
In addition to providing you with the necessary theoretical knowledge and data-driven techniques and methods to succeed in a digitized economy, the M.Sc. Data Analytics & Decision Science also offers detailed insights into the most popular application areas.
An important element is the strong focus on applied data methods, which enables graduates to understand, recognize and react to real-life situations in the companies where they will work.
Healthcare Analytics
After successfully completing this module, you will have a solid understanding of classical management problems arising in health care systems and how to solve these problems with the help of optimization and statistics.
Marketing Analytics
Gain technical marketing-related knowledge such as forecasting models, basics of choice-based optimization or revenue management and pricing using advanced data analysis techniques.
Climate Analytics
Become familiar with advanced concepts in energy and climate systems economics. Learn how to understand climate and energy-related problems arising in companies and gain advanced knowledge in modeling interactions between climate, energy, and economics.
Financial Analytics
Build up a solid understanding of descriptive, predictive and prescriptive methods for the analysis of financial data and decision-making in finance. Learn how to create and interpret financial models to analyze and forecast financial performance, investment opportunities and assess risk.
What Our Students Say
Ajit Gupta
The DDS Analytics Project provides the hands-on experience of the theory we learned before. We had the opportunity to work in a team to solve a complex real-world problem, interact with experts on the subject, and complete the project from scratch. I enjoyed working on a current problem in the industry and learning new skills.
Paul Martinez
I found it very interesting that the M.Sc. program combines Data Analytics and Decision Science, as decision-making is a crucial part of leadership roles. I didn't see this combination highlighted as explicitly in other Master's programs.
Cristian Castro Alvarez
I chose Germany, and this program in particular, because it offers this highly technical package of courses plus direct links to industry.
Gabrijela Juresic
I have learned to much in such a short time and have also developed personally.
Academic DirectorMeet the Academic Director of the Program
Info-Paper
After submitting the form, you will receive the info-paper on the M.Sc. Data Analytics & Decision Science directly via e-mail.
Analytics Project: Make Your Knowledge a Reality
This module is one of the highlights of your studies! You will go through an entire analytics project and learn how to apply your theoretical knowledge to an actual optimization problem. Starting by identifying the individual business need, you can then apply your machine-learning methods and operations research techniques to collect, evaluate, analyze, and interpret data. At the end of the module, you will present your solution to business representatives and directly receive valuable feedback. This project is the ideal preparation for your internship later in your studies!
On-Demand WebinarInfo-Session M.Sc. Data Analytics & Decision Science
Learn more about the study content from the academic director Prof. Dr. Michael Schneider first-hand!
Admission RequirementsWho We Are Looking For
Please check if you fulfill all the admission criteria for the program. Note that we give preference to applicants who completely submit the necessary documents for the verification.
- Degree completed in Engineering or Science in a related STEM field (science, technology, engineering, mathematics)
- At least 125 credit points mathematics and/or natural sciences (e.g. chemistry and/or physics) and/or computer science and/or engineering including a minimum of 15 credit points in the fields of higher mathematics or statistics, database and information systems, programming, algorithms and data structures, complexity theory, quantitative methods/operations research
- Programming skills are beneficial for admission
- At least 1 year of professional work experience
- TOEFL Internet based minimum of 90 pts. or
- IELTS (Academic) test minimum overall band 6 pts.,
- For German applicants: A certificate attesting English language skills at level B2 of the Common European Framework of Reference for Languages (CEFR). This proof is provided, for example, by the submission of a German Abitur certificate, which shows that English has been continuously taught with at least sufficient marks.
Exemptions for the language requirements are only applicable for nationals or first degree holders from the USA, the UK, Canada, Ireland, New Zealand, and Australia.
- CV
- Motivation letter
- At least one letter of recommendation
- Degree certificate
- Transcript of records
- Proof of professional experience of at least 1 year
- Translation of submitted documents (if your documents are not in English or German)
- Not mandatory: Other proof of performance/assessment, e.g. German language certificate, further qualifications/certificates
Optional for application (mandatory for enrollment):
- APS certificate (for Chinese, Indian and Vietnamese applicants)
- English language certificate
Apply Now
AmbassadorsMeet Our Students
EventsUpcoming Info Sessions
FAQFrequently Asked Questions
You require a first degree in a STEM related field with at least 125 ECTS plus an academic proof of at least 15 ECTS in one or more of the following areas: Higher Mathematics and Statistics, Databases and Information Systems, Programming, Data Structures and Algorithms, Computability and Complexity, Quantitative Methods / Operations Research. There are no specific programming skills required per se. However, Python, C++, and Julia can be valuable programming languages to know, and it is certainly beneficial to indicate them in your application.
Yes, our Career Service and Study Management team offer you guidance and support in the form of personal consultations, compass meetings, CV checks or other workshops to help you find and organize the right internship on time.
RWTH Business School is RWTH Aachen University's further education provider in the field of management. All degree programs are offered exclusively for its students and combine excellent, interdisciplinary, academic teaching with practice-oriented insights. Unlike in consecutive degree programs, students at RWTH Business School already bring professional experience with them. This not only creates an educational experience, but also an intensive exchange at eye level and an exciting professional network. This experience is additionally supported by studying in smaller groups with a special closeness to the lecturers. All this and many other exclusive services such as extensive career services, company excursions and events make the study program special. Academic responsibility lies with the professors of the Faculty of Business and Economics. Students receive a degree from RWTH Aachen University.
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