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 and maintain Aurora’s suite of energy market models
- Work closely with our research and consulting teams to derive insights from model
results - Contribute to continuously improving how the modelling team operates
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
What we offer
- The opportunity to substantially influence major decisions in the energy sector
- Direct engagement with clients through Aurora conferences, workshops and
webinars - The opportunity to grow into a publicly visible industry expert
- A fun, informal and international work culture
- An office in the centre of Oxford with coffee, fruit and snacks available in the office
- A competitive salary package
- Access to the Aurora Academy, our training programme offering a range of
opportunities to develop your skills
At Aurora we 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. Please talk to us at interview about the flexibility we could offer and we will explore what’s possible for the role.
