Analyze heterogeneous data sources (e.g., movement patterns, speech usage, interaction histories) to identify relevant usage patterns
Develop predictive models to detect situations of need in technology-assisted everyday scenarios
Derive and validate data-driven recommendations for action based on AI-powered systems
Evaluate the impact of recommendations in field trials using quantitative data

Proven experience modeling human behavior patterns or contextual data
Proficiency in Python and libraries for classification, clustering, and time-series analysis
Familiarity with impact evaluation methods, particularly in social contexts
Ability to critically interpret data models within their broader social context
Willingness to engage in iterative modeling closely tied to real user contexts
German language proficiency at C1 or C2 level is mandatory
Experience with Explainable AI in the context of behavioral decisions is desirable but not required
Experience analyzing smart-home or IoT data
Foundational knowledge in human-centered machine learning
Ability to integrate qualitative data (e.g., diary studies) into quantitative models
Experience with co-creative evaluation processes

Passionate colleagues in an open company culture with flat hierarchies
Professional and personal development opportunities, actively supported and encouraged
Room for personal responsibility and the freedom to pursue your own ideas
Flexible and family-friendly working hours
A passionate team actively shaping a socially and environmentally conscious future

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