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Niche HPC and energy-modelling skills plus seniority limit candidates, but metro locations and hybrid role increase interest.
Role combines transferable automation skills with domain-specific energy modelling, yielding medium cross-industry transferability.
Multiple mandatory technical skills (HPC, pipelines, SQL/NoSQL, Git, LLM integration) imply medium strictness.
Support Chief Modelling Engineer to enhance model operation workflows including data collection, HPC computing, and model development principles.
Design, implement, and maintain automation routines for modelling workflows, including data workflows, quality assurance, API data extraction, HPC job configuration, and workflow monitoring.
Develop internal tools for version control, continuous integration, testing, and build dashboards for performance monitoring; integrate LLM components into workflows for automation and summarization.
Bachelor's and/or Master's degree in computer science, software engineering, data science, or related quantitative field.
Experience managing large databases and data pipelines using SQL and at least one NoSQL technology.
Proficiency in automation tools and scripting (Python, shell scripting, R) and experience with HPC/cluster computing and parallel processing.
Experience with API-based data extraction, Git/GitHub workflows, and visualization tools like Power BI. Work Experience Required: Not explicitly mentioned in the JD.
Experienced in large-scale energy, environmental, or economic modelling automation and data management workflows.
Skilled at operating and configuring HPC or cluster environments for running complex simulations and batch jobs.
Comfortable working collaboratively with modelling and data science teams to apply automation, use LLM tools, and ensure best practices in workflow orchestration.