Working Student, Data Science / Research (m/f/d)

Company Description Muris builds decision software for agricultural supply chains. A processing plant runs around the clock and must never run out of raw crop, while weather, traffic, and trucks change by the hour. Muris is the decision layer between field and factory: we turn live operational data into the planning and scheduling decisions that keep harvest campaigns running. By improving how raw material flows from field to plant, we help make food production more resilient and efficient. The team works on concrete, high-stakes problems in modern agriculture and logistics.

Role Description As a Working Student in Research / Data Science (m/f/d), you will formulate, test, and improve the AI, statistical, and mathematical models behind our decisions, using state-of-the-art AI tools. Every model is tied to a real production process, such as inventory management or vehicle scheduling. On a day-to-day basis, you will explore and validate operational datasets, build and benchmark model variants (from simple statistical baselines to ML and optimization approaches), quantify uncertainty, and stress-test results against real-world data. You will document your findings in rigorous, reproducible reports that directly inform what we build into the product. You will work closely with the founding team, with real ownership of your research questions from problem formulation to final report.

This is a part-time working student position (20 hours per week) based at Delta Campus Berlin, starting September 2026.

Qualifications

• High agency and curiosity: you take a vague question, structure it, and drive it to a defensible answer.
• Research experience you have formulated a quantitative question, designed an analysis or experiment, and written up the results (e.g., thesis, research assistantship, or publication).
• Solid foundation in statistics: model validation, baselines and benchmarks, and honest quantification of uncertainty.
• Knowledge of optimization or machine learning methods (e.g., forecasting, state estimation, scheduling and routing problems) and an interest in applied research.
• Proficiency in Python and SQL for data exploration, modeling, and building reproducible analysis pipelines.
• Strong analytical thinking and the ability to communicate quantitative findings clearly and concisely, in writing.
• Enrollment in a relevant degree program (e.g., Economics, Physics, Mathematics, Statistics, Data Science, Computer Science, Operations Research, Engineering, or a related field) and eligibility to work as a working student in Germany.
• Interest in agri-food, logistics, or supply chain topics; experience with time-series or geospatial data is a plus.

How to apply

• Send your CV and cover letter to [email protected].