Chief Energy Modeller
The Chief Energy Modeller will work together with various business lines to develop short to long-term assessments of future environmental commodities demand growth at the sectoral level, understanding the main drivers and key uncertainties.
- Lead the build out and maintenance of demand models for different environmental commodities based on the analysis of sectorial trends to guide trading and origination strategies;
- Assesses the nature and scale of environmental commodities displacement of fossil fuels, with a special focus on the transport and heating sectors;
- Contribute to formulation of the STX view on environmental commodity markets, working with trading and business analysts to develop one consistent view;
- Manage data sources within the trading, policy and research and analytics teams to ensure accurate reporting and consistent demand assumptions across the organization;
- Articulate how the policy and regulatory frameworks in the environmental commodities affect the commodities demand mix. Model which commodities will be the ‘winners’ and ‘losers’ of new policies and regulations;
- Prepare comprehensive, thought-provoking market analysis and research reports to present to internal stakeholders and external clients;
- Attending conferences to contribute to the growth of the company’s network;
- Provide mentorship and coaching to other analysts.
- Solid demonstrable analytical experience in energy markets at a research/business intelligence company (S&P Global Commodity Insights, Energy Aspects, Rystad Energy) or consultancy;
- Fundamental demand modelling experience (building and maintaining complex models, working with statistical tools, regression modelling);
- Strong interest in and knowledge of the EU policy agenda supporting environmental commodities;
- You are passionate for in-depth data analysis and studying environmental commodities markets;
- An innate ability to identify key trends in large datasets;
- Successful track record in producing original market insights;
- An advanced level of Excel is necessary, Python/SQL skills would be advantageous;
- Relevant master’s degree, e.g., Economics, Business, Finance.
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