Quantitative Analyst

Evolve Energy (Evolve Energy Supply Limited); Lytham St Annes; Hybrid; GBP 70,000 - 100,000; Full time

Job summary

Evolve Energy is seeking a highly analytical Quantitative Analyst to join our Trading & Renewables team in a hybrid role with up to 3 days in the Lytham Office. You will build models and tools to improve trading decisions, forecast demand and analyse risks across power, gas, and renewable assets.

You will work with traders and commercial teams to translate data into actionable pricing recommendations, develop scenario analyses and improve forecasting accuracy under varying market conditions.

Qualifications

• Strong analytical mindset with the ability to interpret large datasets and derive actionable insights.
• Experience applying statistical methods to forecasting and risk assessment.
• Ability to build robust quantitative models and tools for trading and renewables decisions.
• Comfortable communicating complex analysis to commercial teams and traders.

Responsibilities

• Develop quantitative models to support trading, hedging and procurement decisions.
• Analyse portfolio positions, hedge coverage and exposure across delivery periods.
• Develop tools to quantify volume, price, shape and imbalance risk.
• Back-test forecasting methodologies and monitor model performance.
• Translate quantitative outputs into pricing recommendations for commercial decisions.

Skills

Advanced Excel

Statistical analysis

Forecasting

Data modelling

Problem solving

Stakeholder management

Job description

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

Introduction

Love spreadsheets? Fascinated by numbers? Enjoy solving complex problems?

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.

Role Purpose

Reporting to the Head of Trading & Renewables, you'll play a key role in developing the quantitative models, forecasts and analytical tools that support our trading and renewable energy activities. 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.

Duties and Responsibilities

• Develop quantitative models to support power and gas trading, hedging and procurement decisions


• Analyse portfolio positions, hedge coverage and exposure across different delivery periods


• 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


• Analyse the relationship between wholesale prices, demand, renewable generation, weather and system fundamentals


• Develop and improve electricity and gas demand forecasting models across customer portfolios


• Analyse forecast versus actual consumption and identify the drivers of forecast error


• Quantify the financial impact of forecast error and imbalance exposure


• Analyse cashout and imbalance performance and identify opportunities to reduce costs


• Incorporate weather, seasonality, calendar effects and customer behaviour into forecasting models


• Back-test forecasting methodologies and continuously assess model performance


• Analyse historical generation profiles, load factors and expected future production


• Calculate and monitor capture rates, capture prices and capture factors for renewable assets


• Model generation shape against wholesale market prices and customer consumption profiles


• Support the valuation and structuring of PPAs, CPPAs and renewable supply arrangements


• Analyse customer-to-generation matching, including half-hourly generation and consumption profiles


• Develop scenario analysis around curtailment, negative pricing and renewable cannibalisation


• 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

Essential personal skills and experience

• 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


• Strong stakeholder management and communication skills


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


• Strong analytical thinking with the ability to interpret large datasets and draw meaningful conclusions


• A naturally curious mindset that enjoys questioning assumptions and finding better ways of doing things


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


• High attention to detail and a structured approach to solving problems

The ideal candidate

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 won’t just produce numbers – you’ll be interested in understanding why something has happened, what it means for the portfolio and what we should do next.

You’ll enjoy working closely with traders and wider stakeholders, challenging assumptions and communicating complex analysis clearly and in a way that is commercially relevant. 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. We’re equally interested in candidates with strong quantitative capability who are excited by the opportunity to apply their skills within the energy and renewables sector.

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.