About the job
As a Mission Analysis Engineer within our Reusability Program, you will be responsible for modeling and optimizing ascent, reentry, and recovery strategies for our advanced launcher systems. Initially, you will support the European Space Agency (ESA) reusability studies, transforming insights from Spectrum tests into comprehensive mission-level performance assessments and constraints. Your expertise will be crucial in conducting trajectory optimization and Monte Carlo analyses to mitigate risks associated with key design decisions. The outcomes of your work will directly influence vehicle architecture, flight dynamics, and overall program strategy.
Your Role in Our Space Mission
- Execute end-to-end mission and trajectory optimization for ascent, reentry, and recovery scenarios, structuring complex problems for multidisciplinary analysis and providing actionable performance insights to guide system-level decisions.
- Perform trajectory analyses and Monte Carlo simulations to evaluate sensitivity against dispersions, environmental variations, and vehicle uncertainties.
- Engage in mission planning and performance assessments for near-term demonstrators and future Heavy-Lift Vehicle (HLV) configurations.
- Lead multidisciplinary design optimization (MDO) studies and explore design spaces to integrate propulsion, aerodynamics, structures, mass properties, thermal constraints, guidance, navigation, and control (GNC) effects, comparing mission-level outcomes across different vehicle configurations and recovery concepts.
- Maintain and enhance mission analysis models and workflows, ensuring setups are consistent, traceable, reproducible, and scalable, resulting in clean analysis outputs.
- Create high-quality mission analysis documentation for internal reviews and ESA deliverables.
- Coordinate mission-related inputs with specialists in propulsion, structures, fluids, GNC, and systems to ensure coherence and technical consistency in mission assumptions.
- Support program-level decision-making by delivering structured results, scenario comparisons, and data-driven recommendations.

