About the role
Experience: Approximately 5–10 years of relevant professional experience, ideally
combining applied data science, scientific software development and deployment of decision-
support applications.
Preferred Educational Background: Master's degree in Computer Science, Software
Engineering, Computer Engineering, or a related discipline, preferably with experience
developing software applications for scientific, or environmental analysis.
Essential Competencies
• Scientific software engineering: Ability to translate scientific, engineering and
economic models into modular, reusable and maintainable software applications.
• Graphical user interface (GUI) development: Experience developing intuitive,
interactive web-based applications, dashboards and visualisation tools that enable
users to interact with complex analytical models.
• Backend development and model integration: Ability to integrate computational
models with application backends, develop APIs and manage model execution, data
processing and analytical workflows.
• Data integration: Experience managing structured and unstructured datasets,
integrating information from multiple sources and working with relational or
geospatial databases.
Desirable Specialised Capabilities: Experience with one or more of the following would be
particularly valuable:
• Development of web-based scientific applications
• Backend application development.
• Development of interactive dashboards, analytical platforms and automated reporting
tools.
• Experience with SQL, APIs and cloud-based data processing.
• Experience developing scalable, modular software architectures that allow analytical
models to operate independently of the graphical user interface.
Preferred Professional Experience: Candidates should preferably have undertaken applied
scientific software engineering or computational-modelling assignments. Experience in
developing and deploying interactive, GUI-based decision-support tools or analytical
software platforms for industry, government or research institutions would be particularly
valuable.
Candidates should demonstrate the ability to develop end-to-end applications, integrating
scientific or analytical models with backend computational engines and intuitive user
interfaces, while ensuring that the underlying models remain secure, maintainable and
accessible through controlled application interfaces.
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