Graduate Quantitative Analyst, Energy Aspects

• You will be able to work independently, as well as be capable of planning and prioritising to achieve success
• Minimum Master’s degree in a quantitative field (Mathematics, Physics, Computer Science, Engineering, Economics, Finance)
• Excellent programming skills in Python / R and strong familiarity with numeric libraries and methods
• Strong expertise in time series analysis (financial econometrics and/or ML)
• Good communicator and synthesiser of complex material (written and spoken)
• Core data science and data management skills. Cleaning, processing, merging and presenting
• Ability to work independently to solve technical challenges with practical problem-solving skills, to tight deadlines

Desirable

• Energy Aspects is seeking a Quantitative Analyst to join our derivatives analytics team
• This is a fantastic opportunity for an analyst with a solid technical background and commercial outlook to be part of our successful growth story
• The successful candidate will quickly take on a range of responsibilities and will contribute to the full life cycle of our work, from original quantitative research development, building and maintaining models, carrying out detailed analysis, delivering compelling market coverage, and delivering our core views to clients
• The position will be responsible for preparing and contributing to our publications, with a focus on the paper side of commodity markets
• This will involve you carrying out a comprehensive analysis of futures market pricing developments, futures and options participant flows and positioning analysis, and integrating this with our wider global analysis to create forward-looking tradeable views
• You will be expected to consistently produce high standard deliverables to tight deadlines, meeting the needs of our demanding client base
• This position will require flexibility and the drive to go beyond the core hours when needed, ensuring we all fulfil our goals
• Preparing and contributing to many of our publications
• Modelling commodity futures/options market participants
• Modelling market impact of key commodity price drivers
• Building and maintaining datasets and code base