SysML Data Analyst Digital Engineering

We are seeking a SysML Data Analyst to support our transition to SysML v2-based system modelling as part of our Digital Engineering transformation. This role will play a foundational part in shaping the future modelling ecosystem by developing a SysMLv2-compliant library from our existing DSL (Domain-Specific Language) and enhancing user experience through guided, AI-augmented modelling workflows.

You will work at the intersection of systems modelling, data abstraction, and AI-assisted usability, helping build the groundwork for future modelling productivity tools like an AI Copilot for modelling.

Key Responsibilities

SysMLv2 Migration & Modelling Support

• Develop a SysMLv2 library that reflects the existing DSL data model, currently implemented in UML using MagicDraw.
• Support the transition of modelling tools (e.g., from MagicDraw to Siemens System Modeller or IBM Rhapsody SE) and their integration into Teamcenter (evaluation in progress).
• Ensure semantic and functional alignment of DSL with tool agnostic SysMLv2 language.
  
  

• Implement user-friendly, guided modelling workflows to simplify and streamline system modelling.
• Introduce modelling of DSL users’ context, interactions, workflows and create abstractions that make modelling more intuitive for end users.
• Collaborate with domain experts to understand pain points and define actionable usability improvements.
  
  

• Contribute to the design and evolution of AI-assisted modelling support, such as a Modelling Copilot.
• Help build foundational datasets and define patterns that AI systems can learn from to offer real-time modelling suggestions and guidance.
• Work with data scientists and AI engineers to define feedback loops and learning mechanisms based on user interactions.
  
  

• Bachelor’s or Master’s degree in Computer Science, Mechatronics, or related field.
• 12+ years Industry experience with minimum 5 years hands-on experience with SysML, UML, and system modelling tools such as MagicDraw, Cameo, Rhapsody, or Siemens System Modeller.
• Strong understanding of model-based systems engineering (MBSE) principles and DSL-based modelling.
• Familiarity with SysMLv2 concepts, structure, and its advantages over UML-based approaches.
• Knowledge of Teamcenter, model repositories, and integration between modelling tools and PLM systems is a plus.
  
  

• Experience in AI/ML-based tool development or collaboration with AI teams to deliver smart, learning-enabled features.
• Exposure to usability design, workflow simplification, or UX/UI patterns in system modelling environments.
• Ability to communicate modelling principles and usability enhancements effectively to both technical and non-technical stakeholders.
  
  

• Opportunity to work at the cutting edge of Digital Engineering and AI-assisted modelling.
• High visibility and strategic importance in shaping future modelling practices.
• Flexible engagement model with the potential to expand based on 2026–2027 program needs.