Student Assistant to support us with data science tasks

Technische Universität München
Heilbronn, Germany
about 1 month ago

Role details

Contract type
Permanent contract
Employment type
Part-time (≤ 32 hours)
Working hours
Shift work
Languages
English, German
Job source

Tech stack

Artificial Intelligence Data Analysis Computer Programming Web Scraping Cursor (Graphical User Interface Elements) Digital Content Python (Programming Language) Systems Integration Pytorch Large Language Models Multi-Agent Systems Deep Learning
+1 more
Information Technology

Job description

For the TUM School of Management at the Heilbronn Data Science Center, TUM Campus Heilbronn, we are looking for a Student Assistant (m/w/d) to support us with data science tasks for 9-20 hours per week.

Requirements

We are looking for a motivated student with a strong interest in applying data science methods to real-world research questions and practical challenges. You should enjoy working independently, learning new tools and methodologies, and approaching complex problems with curiosity and critical thinking., * Experience in extracting, cleaning, and analyzing data

  • Prior experience in computer programming and/or statistical programming; Python skills are particularly desirable
  • Ability to conduct research, document your work carefully, justify methodological decisions, and learn from existing literature
  • Strong organizational and communication skills
  • Very good English communication skills, as the working language of this position is English

Additional qualifications that would be an advantage :

  • Experience with web scraping and integrating LLM APIs, such as OpenAI or OpenRouter
  • Strong mathematical, statistical, or computer science training
  • German language skills
  • Experience or interest in one or more of the following areas:

  • Manufacturing, marketing analytics, economics, transportation, or smart cities
  • Scheduling and optimization, for example production scheduling
  • Development of simulation environments
  • Digital content analysis
  • Large language models and multi-agent systems
  • Spatio-temporal deep learning and AI, especially with PyTorch
  • Local LLM deployment
  • AI-assisted coding tools and agentic coding workflows, such as Claude Code, Cursor, or Codex CLI

Benefits & conditions

Hands-on experience with real-world data science projects in an academic and interdisciplinary environment. Flexible working hours that can be aligned with your study schedule. The opportunity to develop practical skills in data analysis, programming, and research-oriented documentation.

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