The English-language postgraduate Master's programme Project Management and Data Science (MPMD) is looking for a lecturer in advanced computational data analytics with Python from summer semester 2026. The teaching assignment comprises 50 teaching units à 45 minutes à 100,- Euro per semester.

The study programme aims to qualify students for complex leadership roles in national and international companies and institutions by providing application-oriented teaching. A detailed, professional eLearning course is available. Graduates of the programme can successfully lead data-driven projects in an international context.

After successful completion of this course:

• Students can explain the statistical tasks or approaches  necessary to implement in each step of the CRISP DM process in order to build reasonable data mining models.
• Students are familiar with a wide range of different Data Mining concepts and models – see details below
• Students know the systems and implementation requirements of data mining approaches/models, and are able to offer detailed and technically proficient explanations of their respective advantages and drawbacks.
• Students have proven their ability to apply these data mining approaches in concrete and practically relevant scenarios. This requires them to perform analysis, critically assess the results of their models and, if necessary, select alternative approaches to obtain optimum solutions to the problem at hand.
• Students can enrich data by applying feature engineering.

The subjects covered in the teaching unit include:

• Introduction to Data Mining
• Cross Validation
• Rough Dimensionality Reduction
• Outlier Removal
• Transforming Variables
• Imputation of Missing Values
• Feature Reduction, Selection and Factor Analysis
• Balancing and Resampling
• Logistic Regression
• Confusion Matrix
• Decision Trees
• More Classification Methods such as SVM
• Cluster Analysis

Python is employed for data preparation and modelling (including team work in Python, e.g. with Github). Teaching should be practice-oriented and include practical tasks and group work.

• Classes will take place in weekly sessions from mid-February to beginning of July
• The lessons will take place online via Moodle and videoconferencing
• The language of instruction is English
• Modern eLearning environment and accompanying e-learning materials will be provided
• A professional e-learning team will support you in adaption and implementing existing and new teaching materials

• Proven track record in data analysis with Python
• Very good command of written and spoken English
• (Online) teaching experience
• University degree at Master’s level
• Ability to consider and integrate gender and diversity aspects