Taikonauten

Data Scientist – Mensch

Taikonauten

full-time

Posted on:

Location Type: Hybrid

Location: BerlinGermany

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Tech Stack

About the role

  • 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-supported 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

Requirements

  • Significant 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 reflect on and interpret data models in a societal context
  • Willingness to engage in iterative modeling closely tied to real user contexts
  • Nice to have, but not required: experience with Explainable AI in the context of behavioral decision-making
  • Knowledge of Smart Home or IoT data analysis
  • 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
Benefits
  • Passionate colleagues in an open corporate culture with a flat hierarchy
  • Opportunities for professional and personal development, supported and encouraged
  • Space for autonomy and your own ideas
  • Flexible and family-friendly working hours
  • A passionate team actively shaping a socially and environmentally conscious future

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
Pythonclassificationclusteringtime series analysisimpact evaluation methodsdata modelingExplainable AISmart Home data analysisIoT data analysisHuman-Centered Machine Learning
Soft skills
critical reflectioninterpretation of data modelsiterative modelingengagement with real user contextsco-creative evaluation processes