Energy Modelling Analyst
Contribute to energy modelling efforts in Oxford, UK. Develop analytical tools, enhance methodology, analyze data, and provide insights to clients. Ideal for recent MSc or PhD graduates.
Based in Oxford, you will contribute to our energy modelling efforts by developing analytical and computational tools, enhancing our modelling methodology, analysing data, formulating recommendations on future trends, and conveying insights to enhance clients’ decision making. The positions have a focus on modelling energy commodities (notably electricity) markets and suit a recent university graduate (MSc or PhD).
Key Responsibilities
- Develop the models that drive Aurora's software solutions, such as Origin and Chronos, to provide cutting-edge insights into the energy market;
- Collaborate closely with our research and advisory teams to derive insights from model results, ensuring that they enhance clients’ decision making;
- Customise and adapt models to reflect the intricacies of specific energy markets, while building analytical tools to enhance Aurora’s technical suite;
- Actively contribute to the continuous improvement of processes within the broader modelling team.
Skills, Knowledge and Expertise
Required attributes
- Relevant degree in Economics, Engineering, Mathematics, Computer Science or other quantitative field from a top university;
- Exceptional problem solving skills and analytical ability;
- Ability to collect, analyse and interpret complex quantitative data and information;
- Knowledge of one programming language, e.g. C++, Matlab, Python, R, Java;
- Strong interpersonal skills, and a great team player.
Desirable attributes
- Relevant Master’s degree or PhD;
- Knowledge of and interest in energy markets, and a belief that well-designed models significantly improve decision making;
- Knowledge of statistical and/or optimization techniques;
- Knowledge of an algebraic modelling language, such as GAMS (preferred) or AMPL.
关于这个角色
May 15, 2024
全职
公司
Nov 15, 2024
现场
Oxford, United Kingdom
Entry Level
UTC+00:00
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