Senior Model Automation Engineer

The Role

Energy, Economy and Environment modelling as part of WSP plc develops and maintains large-scale applied mathematical models that represent the energy, environment and economy, supporting quantitative analysis and policy design. Its integrated modelling tools provide informed, transparent and robust analysis as well as recommendations for its high-profile clients which include the European Commission, national governments, energy regulators and a number of private companies in the energy and transport sectors, financial institutions and strategic consultancies.  This role is about supporting the Chief Modelling Engineer to improve the design of the models operations (data collection/harmonisation, database access, HPC computing, model development principles).

• Suggest, design, and implement modelling automation routines to improve workflow efficiency in cooperation with the energy and economic modelling teams.
• Design and maintain data workflows and quality assurance processes for large modelling databases (inputs, intermediate outputs, and results).
• Develop and operate automated data extraction pipelines via APIs to feed models with timely and consistent datasets.
• Configure and use HPC/cluster computing and parallel processing solutions to run large-scale simulations and batch model runs.
• Develop and maintain internal tools and scripts for workflow orchestration, including scheduling, monitoring, and logging of model runs.
• Help develop and maintain internal tools for version control, continuous integration, unit testing, backup and documentation using Git/GitHub and similar applications.
• Build dashboards and visual analytics in Power BI or equivalent tools for monitoring model performance, scenario results, and key indicators.
• Integrate LLM-based components into modelling workflows for data processing, semi-automated calibration, and result summarization.
• Liaise with the Data Science group and modelling teams for the exchange of tools and methods, ensuring best practices in automation and data management are adopted.
• Assist with troubleshooting and problem-solving when issues arise in automated pipelines, HPC jobs, or LLM-powered tools.

Key competencies and experience

• Hold a BSc and/or MSc degree in computer science, software engineering, data science, or an adjacent quantitative field.
• Experience in managing large databases and data pipelines, including SQL and at least one NoSQL technology.
• Demonstrated experience using automation tools and scripting/programming languages (e.g. Python, shell scripting, R; experience with GAMS or similar modelling languages is an asset).
• Experience with automated data extraction and integration via APIs.
• Experience using or administering High-Performance Computing (HPC) or cluster environments, and familiarity with parallel processing.
• Familiarity with Git/GitHub workflows for collaborative development and version control.
• Experience with Power BI or equivalent visualization/BI tools.
• Demonstrated experience or strong interest in applying LLMs in technical environments (e.g. auxiliary tools for data processing, summarization, or code assistance).
• Be proficient in verbal and written communication in English.
• Have a detail-oriented and problem-solving mindset, a collaborative attitude and willingness to learn and adopt new tools.

BGV:

• Employment with WSP India is subject to the successful completion of a background verification (“BGV”) check conducted by a third-party agency appointed by WSP India.
• Candidates are advised to ensure that all information provided during the recruitment process — including documents uploaded — is accurate and complete, both to WSP India and its BGV partner”.