Management & Data Science (MSc)

This English-taught MSc in Management & Data Science at Leuphana University Lüneburg is designed for students who want to work with large, complex data sets and build statistical models using current information technologies. The programme combines practical, application-oriented training with research opportunities so you can apply analytical methods directly to real management problems.

As global markets and organisations become more data-driven, traditional decision-making and individual experience are no longer sufficient. This interdisciplinary programme links management, data analysis, and information systems to equip you with the skills to design innovative solutions for information-driven organisations and to manage the complexity of modern business environments.

Demand for data scientists is rising across industry, government and academia. By blending technical analytics with managerial insight, this MSc prepares you for careers in business, public administration, and research — particularly roles that require turning large-scale data into actionable management solutions.

Key facts and requirements

• Degree: Master of Science (MSc)
• Field: Interdisciplinary (management, data analysis, information systems)
• Language of instruction: English
• Location: Lüneburg, Germany
• Target students: those who want to analyse massive/complex datasets and design statistical models using modern IT
• Typical career paths: business, public administration, research

Curriculum overview and what you will learn

Across the programme’s semesters you progress from core technical foundations to applied, team-based research and a final thesis. In the first semester you build a strong base in the mathematics and tooling needed to extract knowledge from data, along with an introduction to data economics. The second semester focuses on large-scale data technologies and advanced modelling: storage and mining of massive datasets, probabilistic modelling, network analysis, forecasting and simulation.

In the third semester you undertake a substantial, team-based research project that addresses real-world, data-intensive problems—often carried out in collaboration with companies—and you deepen your understanding of data privacy and ethics. This semester also includes two electives to specialise further (or up to two optional modules from other Management & Entrepreneurship majors). If you plan to study abroad, the third semester is the recommended time to do so. The programme’s management strand comprises three modules to develop your business and leadership skills, while an interdisciplinary complementary studies component (also three modules) strengthens academic research skills and cross-disciplinary problem‑solving approaches. In the final semester you complete your Master’s dissertation and participate in the accompanying Master’s Forum.

Key modules and expected learning outcomes

• Core foundations: mathematics for data science; practical mastery of data analysis tools; understanding data economics.
  • Outcome: ability to preprocess, analyse and interpret datasets using appropriate quantitative methods and software.
• Large-scale and advanced methods: storage and mining of massive datasets; probabilistic modelling; network analysis; forecasting and simulation.
  • Outcome: competence to design and implement models and systems for big-data scenarios and to produce reliable forecasts and simulations.
• Research project (team-based, industry-linked): applied investigation of data-intensive questions with scientific rigour.
  • Outcome: experience in project management, collaborative research, translating business problems into data solutions.
• Ethics and privacy: focused modules on data privacy and ethical issues.
  • Outcome: capacity to recognise, evaluate and manage privacy and ethical considerations in data projects.
• Electives and cross-major options: two electives for specialization; up to two optional modules may be taken from other Management & Entrepreneurship majors.
  • Outcome: tailored skill profile aligned with personal or sector-specific interests.
• Management modules (3) and Interdisciplinary complementary studies (3): business, academic and cross-disciplinary methods.
  • Outcome: integrated ability to bridge technical data skills with management thinking and interdisciplinary problem solving.
• Master’s dissertation + Master’s Forum: capstone research and presentation.
  • Outcome: demonstrated independent research capability and communication of results to academic and professional audiences.

This structure is designed to prepare you for roles that combine data science and management—such as data-driven strategy, analytics leadership, or applied research in industry—while offering flexibility (electives, study‑abroad option) to shape the degree to your career goals.

Graduates are prepared for roles that bridge data science and management—such as data scientist, analytics manager, business intelligence specialist, or policy analyst—in private companies, public administration and research institutions. The programme’s combination of technical skills, organisational understanding and industry-linked projects enhances employability across sectors that rely on data-driven decision making.

The applied, interdisciplinary training and emphasis on data ethics also position graduates well for research-oriented careers or further doctoral study, especially where teams need expertise in both analytics and organisational implementation.