The English-language postgraduate Master's programme Project Management and Data Science (MPMD) is looking for a lecturer in foundations of data analytics and statistical programming from winter semester 2025. The teaching assignment comprises 48 teaching units à 45 minutes à 80,- (3.840,-) Euro per semester.

The MPMD provides international students with the knowledge to work as data analysts and project managers in national and international companies and to successfully manage international data-driven projects through application-oriented teaching.

The programme has been offered since 2016 and is in high demand internationally. It is open to both students with a data science background and career changers from other fields who can be expected to be highly motivated. Every year, 35 to 40 Master's students from more than 15 countries take part in the 4-semester programme. Graduates of the MPMD are sought after by global players in the industry as well as by start-ups.

The study programme aims to qualify students to take on complex leadership roles in nationally and internationally active companies and institutions through application-oriented teaching. Graduates of the programme are able to successfully lead data-driven projects in international contexts.

The teaching unit on Data Processing and Advanced Regression Techniques with Python is part of module MPMD1.2 Foundations of Data Analytics and Statistical Programming. At the end of this teaching unit, students will be able to competently handle data sets with Python as their analytical tool. They will be familiar with the techniques necessary for data analysis as well as performing correctives thereon. Knowledge of univariate methods of descriptive statistics from a previous teaching unit will be deepened. In addition, students will gain insight into inductive methods as well as multivariate methods. Students will also be able to name the components of an ETL process and explain the basics of using databases. The subjects covered in the teaching unit include:

• Databases and ETL
• Probability Distribution of Continuous and Discrete Random Variables
• Distribution Tests
• Contingency
• Correlation
• Regression
• Assessing Regression Models
• Advanced Regression Modelling
• Python for data preparation and modelling (including team work in Python, e.g. with Github, Scikit-Learn, ML Workflow with Python, data splitting, evaluation, increasing model performance (hyperparameter tuning), building data mining models with restricted complexity and assess their quality using the confusion matrix concept)

Teaching should be practice-oriented and include practical tasks and group work.

• Classes will take place in weekly sessions from mid-November to mid-February
• The lessons will take place on the Treskowallee campus of HTW Berlin in a hybrid form (on campus plus live streaming); part of the lessons can also be taught online
• The language of instruction is English
• Modern classroom equipment 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