Compensation Analyst - Hybrid working in Lytham St Annes

Location: Hybrid working/Up to 3 days in the Lytham Office

At Evolve Energy, we're looking for a highly analytical Quantitative Analyst to join our growing Trading & Renewables team. This role is ideal for someone who enjoys building quantitative models, working with complex datasets and using data to solve real-world commercial and trading problems. You'll work within a fast-moving energy market, applying statistical analysis, forecasting and quantitative techniques to help improve trading decisions, optimise portfolio performance and strengthen our understanding of risk. You'll analyse everything from customer demand and wholesale market movements to renewable generation, imbalance exposure and asset capture rates, turning complex data into clear and actionable insight.

Working across both traditional energy supply and our growing renewable portfolio, you'll help develop the analytical capability behind our trading, pricing and renewable strategies. Whether you're already working within energy or looking to apply strong mathematical, statistical or programming skills to the sector, this is an opportunity to build models and tools that have a direct impact on commercial performance.

This is a hands-on quantitative role for someone who enjoys getting under the skin of complex problems, testing assumptions and using data to understand not only what is happening, but why it is happening and what we should do as a result.

• Develop quantitative models to support power and gas trading, hedging and procurement decisions
• Develop tools to identify and quantify volume, price, shape and imbalance risk
• Analyse historical and forward market data to identify trends, correlations and trading opportunities
• Support trading team with quantitative analysis around hedge timing, products and portfolio optimisation
• Develop scenario and sensitivity analysis to understand portfolio exposure under different market conditions
• Develop and improve electricity and gas demand forecasting models across customer portfolios
• Quantify the financial impact of forecast error and imbalance exposure
• Analyse cashout and imbalance performance and identify opportunities to reduce costs
• Back-test forecasting methodologies and continuously assess model performance
• Calculate and monitor capture rates, capture prices and capture factors for renewable assets
• Analyse customer-to-generation matching, including half-hourly generation and consumption profiles
• Support commercial decisions around new renewable assets and PPA opportunities
• Support the development of pricing methodologies for flexible and structured energy products
• Analyse customer consumption profiles and determine appropriate risk premiums
• Support pricing of bespoke contracts and complex commercial structures
• Perform back-testing of pricing assumptions against realised portfolio performance
• Work with commercial teams to translate quantitative outputs into clear pricing recommendations

A real passion for numbers, Excel and data, someone who enjoys building models, spotting patterns, challenging assumptions and using analysis to crack commercial problems.

Supporting senior team members in formulating strategy, pre-trade analysis, execution, post-trade analysis, allocations, and settlement across multiple strategies.

Advanced Excel skills and the ability to build, improve and maintain robust analytical models.

Strong communication skills with the ability to explain complex analysis in a clear and commercial way.

You’ll be highly analytical, naturally curious and confident working with numbers, with a genuine interest in using data and quantitative techniques to solve complex problems. You’ll enjoy building models, interrogating large datasets and identifying the patterns and relationships that can improve trading, forecasting and commercial decision-making.

You’ll be comfortable using statistical and analytical techniques to understand what the data is telling you and, importantly, translating that analysis into clear, actionable recommendations. You’ll be proactive in identifying opportunities to improve models, automate processes and develop better ways of measuring and managing portfolio performance.

You’ll have previous experience in a quantitative, analytical, data science or modelling-focused role, with a strong grounding in statistics, mathematics, forecasting or data analysis. Experience within energy, commodities, trading or financial markets would be advantageous, but isn’t essential.

If you’re naturally numerical, enjoy solving difficult problems and want to see your models and analysis directly influence real-world trading and commercial decisions, we’d love to hear from you.