Commodity Analyst (City of London)

A leading corporate banking and capital markets organisation is seeking a Commodity Analyst to join their team in London.

Main Purpose of this Role: Commerzbank Corporates clients (CC) is the integrated Corporate and Investment Banking division of Commerzbank AG. CC provides corporate and institutional clients with a broad range of commercial and investment banking products. It is active in Europe’s most important markets with main offices in Frankfurt and London. The business incorporates capital markets activities in commodities, interest rates and foreign exchange with a strong focus on derivatives. It provides clients with capital and debt raising solutions and offers its customers access to a broad range of investment and risk management products across all major asset classes.

The Commodity trading team within Financial Markets (FM) is a product specialist team with the responsibility of Market making and risk managing the whole Commodity products suite of the bank. Our clients are corporates who manage their commodity price risk; and their banks that act as their counterparties when Commerzbank has no relationship with the end-client. We provide tailor-made Commodity hedging solutions to our clients across the globe. We design complex Commodity trading strategies to maximize the value of our client franchise and optimize the P&L for the bank. The Commodities trading team is expanding its capabilities in the gas and power space and is looking for a highly motivated individual with a strong level of intellectual curiosity to join their team in London as a Commodity analyst. Your mandate will be to act as the lead Commodity power and gas analyst for the Commodity business.

Key Activities and Key Competencies:

• Develop technical, market, product and technological expertise in order to expand the business’s capabilities on gas and power fundamental analysis and market making.
• Work with the Head of European energy trading and the Head of Commodity trading to implement, calibrate and maintain the team’s various power and gas pricing/forecast models.
• Act as subject matter expert in gas and power within the bank and promote the franchise with all internal stakeholders.
• Coordinate with Support units, specifically quants and developers, in order to productionize new models.
• Actively promote the Power franchise with Sales teams. Provide accurate and timely market colour on their requests and provide regular trade ideas and market comments.
• Assist in the further automation and digitisation of the gas and power business, coordinate projects, monitor performance against objectives.

Specific tasks will include:

• Support the construction of arbitrage-free Natural Gas curves and Power curves.
• Assess risk sensitivity models and location spread sensitivity models (for both Power and Gas).
• Maintain a fundamental Supply and Demand model for Gas Storage Balances and the Gas Corridor.
• Build stack models in core Power markets and/or delta sensitivity models around Interconnector costs and flows.
• Provide weekly market comments and insights.
• Build a gas storage model.
• Build a Virtual power plant model.

Key Requirements:

• Sufficient years of experience in Data analytics with a proven ability to extract insights from complex datasets.
• Proficiency in programming, preferably Python and SQL.
• Solid comprehension of large language models (LLM) in order to support the desk’s research.
• Ability to utilize advanced data analytics and time series analysis techniques to generate actionable signals for commodities trading.
• Ability to perform data cleaning, transformation, and web scraping to ensure high-quality datasets and insightful analysis.
• Sharp technical understanding of derivatives contracts.
• Strong interest in the various Energy supply and demand fundamentals in Europe.
• Robust understanding of the key end-consumers and suppliers in Europe and the UK.
• Excellent numerical and analytical skills.
• Solid problem-solving abilities.
• Strong commercial mindset and ability to communicate technical insights effectively to stakeholders to facilitate informed decision-making.
• High entrepreneurial attitude required to develop a business.
• The successful candidate is likely to be educated to degree level in Data Science, Mathematics, Physics, Engineering, Econometrics, or a similar highly quantitative discipline.