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# Data Scientist Level 2

- **Company:** Werk op Schiphol
- **Location:** Schiphol, Netherlands (Remote available)
- **Salary:** €4,349.0
- **Contract:** Permanent contract
- **Skills:** Computer Programming, IBM ILOG CPLEX Optimization Studio (CPLEX), Python (Programming Language), Mathematical Programming, NumPy, Operational Data Store, Data Processing, Pandas, Data Pipelines
- **Published:** October 29, 2026
- **Apply:** https://www.werkopschiphol.nl/vacatures/overig/data-scientist-level-2

## About the Role

* MSc in Operations Research, Applied Mathematics, Industrial Engineering, or a related quantitative field
 * Hands-on experience ( with mathematical programming and combinatorial optimization (MIP, LP, CP, or similar)
 * Proficiency with optimization solvers such as Gurobi, CPLEX, or OR-Tools
 * Strong programming skills in Python, including experience with data processing libraries (pandas, NumPy)
 * Ability to model ambiguous, real-world operational constraints rigorously and pragmatically
 * Experience working with large, time-sensitive datasets and event-driven data pipelines is a plus
 * Familiarity with airport or logistics operations is an advantage, but not a requirement

Competencies:

 * Flexibility
 * Expertise
 * Problem analysis
 * Teamwork
 * Communication
 * Result oriented
 * Understanding of company processes
 * Planning and organising, Wo

## Description

This is a combinatorial optimization challenge of significant scale. Every few minutes, the system must evaluate hundreds of incoming flights, assign transport devices (containers and bulk carts) to drivers, allocate baggage flows across multiple hall infeeds, and respect hard constraints such as hall capacity, driver availability, and flight departure times - while minimizing the risk and cost of mishandled baggage for passengers with short connections.

Manual planning and rule-based heuristics are no longer sufficient at this complexity and speed. As a Data Scientist on the BagPRO team, you will work on the mathematical optimization models that power this decision engine, improve solver performance (Gurobi), refine cost functions based on mishandled baggage risk, and translate operational constraints into model logic that drives measurable improvements in ground handling performance.

But it does not end there. You might work on an innovation project in KickstartAI (kickstartai.nl), contribute to our partnerships with various universities to drive innovation and research, or play a fundamental role in our community of practice for data science.
What will you do?

 * Develop and maintain mathematical optimization models that drive real-time baggage flow decisions at Amsterdam Airport Schiphol
 * Improve and tune solver configurations (Gurobi) for performance under tight operational time constraints (solve cycles of 5-10 minutes)
 * Refine objective functions and cost parameters based on mishandled baggage risk, passenger connection criticality, and operational priorities
 * Translate complex ground handling constraints - hall capacities, driver availability, inbound flight schedules - into clean model logic
 * Collaborate with operations managers, baggage flow controllers, and software engineers to validate model outputs against real-world outcomes
 * Analyse post-hoc operational data to identify model gaps and continuously improve solution quality