Apply for the Aurora Energy Research Oxford Graduate Modelling Programme for recent graduates
Closing Date: 3 November 2024
Apply for the Aurora Energy Research Oxford Graduate Modelling Programme for recent graduates
The Aurora Energy Research Oxford Graduate Modelling Programme offers recent graduates an excellent experience and development opportunities through an extensive training programme with high-impact projects.
About Aurora Energy Research
From its academic roots, Aurora Energy Research is a thriving, rapidly growing company, currently serving over 600 of the world’s most influential energy sector participants, including utilities, investors, and governments.
While Aurora Energy Research constantly strive to reach new markets and diversify its product portfolio, Aurora Energy Research is already active across the globe in Asia-Pacific, Latin America, Europe, and North America, working with leading organisations to provide comprehensive market intelligence, bespoke analytic and advisory services, and cutting-edge software. Aurora Energy Research is a diverse team of experts with vast energy, financial, and consulting backgrounds, covering power, hydrogen, carbon, and fossil commodities. With this, Aurora Energy Research provide data-driven intelligence to fuel strategic decisions in the global energy transformation
Oxford Graduate Modelling Programme
Based in Oxford, you will contribute to the energy modelling efforts by developing analytical and computational tools, enhancing the 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.
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
What Aurora Look’s For
Required attributes:
- Relevant degree in Economics, Engineering, Mathematics, Computer Science or other quantitative field
- 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. Python (preferred), C++, Matlab, 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
What is offered
- A fun, informal, collaborative and international work culture
- A competitive salary package
- Access to regular coaching and mentoring sessions and the opportunity to learn from experienced professionals
- Access to the Aurora Academy, our training programme offering a range of opportunities to develop your skills within the responsibilities of your role and within the wider context of the industry
- Access to our Employee Assistance Programme (EAP), offering a complete support network that offers expert advice and compassionate guidance 24/7/365, covering a wide range of personal and professional aspects
- All UK employees are eligible from day one for company paid private medical insurance through
the AXA Business Health scheme
Aurora will consider all requests for flexible working. For most roles, the following types of flexibility are usually possible: a hybrid model of remote and in-office working, part-time hours and flexible start and finish times.
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