Data Scientist
aevoloop GmbH
16 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
IntermediateJob location
Tech stack
Data Auditing
Data Visualization
Data Warehousing
Experimental Data
Raw Data
Software Engineering
Information Technology
Data Analytics
Machine Learning Operations
Data Generation
Job description
Join aevoloop, one of Europe's fast-scaling deep-tech startups, and help accelerate the development of pioneering next-generation plastics through data-driven R&D enablement.
- Establish data warehousing within the R&D department to maximize data efficiency and automate data collection & generation
- Roll out and manage an electronic lab notebook system to structurize and collect experimental data for data evaluation and comparison
- Develop customized apps for facilitating processing of raw data of lab instruments and devices
- Generate data visualization and comparison dashboards that allow to compare lab data
- Design and implement concepts for employing modern AI and ML tools to increase speed and output of the whole R&D team, * Real Impact: Help redesign plastics for a truly circular economy.
- Startup Mindset: Flat hierarchies, fast decisions and early responsibility as we scale.
- Team Culture: Join a team of curious minds that challenge each other, collaborate openly and celebrate progress together.
- Growth & Learning: Steep learning curves, regular feedback and room to grow with the company.
- Well-being Perks - Hansefit membership and fresh fruit boost your overall health and well-being.
Requirements
- You successfully completed studying Computer Science, Software Engineering, Data Science, or a related field, preferably with a M.Sc. degree
- You have at least 2 years job experience on data generation and processing in a chemical, biological, or physical context
- You work independently and find joy in interdisciplinary collaboration
- You know how to help yourself when facing technical challenges
- Demonstrated troubleshooting skills and a passion for experimental process optimisation
- You bring a hands-on mindset, structure your work efficiently, and collaborate seamlessly across disciplines - even under the dynamics of a fast-paced start-up environment