Revenue Analyst

Verdian; Madrid; Presencial; EUR 40.000 - 65.000; Jornada completa

Descripción de la vacante

Verdian, a European renewable energy platform, is seeking a Revenue Analyst in Madrid to develop and maintain analytical models for forecasting, market analysis, and revenue optimisation. You will support commercial decisions and collaborate with internal teams to deliver data-driven insights.

The role requires strong quantitative foundations, programming capabilities, and curiosity to deepen energy market understanding while supporting reporting and tool development.

Formación

• Strong quantitative foundations and analytical mindset.
• Programming skills for modelling and data manipulation.
• Ability to translate data into clear insights for decision makers.

Responsabilidades

• Maintain, update, and improve analytical models for forecasting, risk assessment, and market analysis.
• Forecast power prices and perform market analyses to support pricing decisions.
• Assess risks in PPAs and optimize renewable assets (PV + BESS).
• Evaluate commercial strategy and generate revenue forecasts.
• Perform quantitative analyses to support negotiations and short/long-term offtake decisions.

Conocimientos

Quantitative skills

Programming

Descripción del empleo

Verdian is a European renewable energy platform dedicated to delivering clean energy and accelerating the energy transition. Our success is driven by talented people, entrepreneurial thinking, and a culture built on agility, flexibility, integrity, results, and empowerment.

ROLE PURPOSE:

The Revenue Analyst supports Verdian’s revenue activities by developing,

maintaining, and enhancing analytical models and tools used for

forecasting, optimisation, risks assessment, and market analysis. The role

contributes directly to the commercial decision-making process, contract

negotiations, and portfolio optimisation by providing reliable data-driven

insights across multiple energy markets.

Operating within the Revenue function, the role supports analytical tasks

and recurring deliverables under guidance from more experienced team

members. It requires strong quantitative foundations, programming skills,

curiosity, and a willingness to build knowledge of energy market dynamics

while contributing to data preparation, model maintenance, reporting, and

analysis for business decisions. The role works closely with internal

stakeholders, helping translate data into clear insights while developing

technical capability and commercial understanding over time.

KEY RESPONSIBILITIES:

Maintain, update, and continuously improve analytical models used for:

• Power price forecasting and market analysis
• Pricing and assessment of risks associated with Power Purchase Agreements (PPAs)
• Optimisation of renewable energy assets, including solar and battery storage (PV + BESS)
• Commercial strategy evaluation and revenue forecasting
• Perform quantitative analyses to support commercial negotiations and decision-making related to short and long-term offtake arrangements, PPAs, and other energy commercialization activities.
• Deliver regular reporting, dashboards, and market intelligence to management, providing insights on market trends, pricing developments, risks exposures, and key performance indicators.
• Develop new analytical tools, models, and methodologies that improve decision quality, forecasting accuracy, operational efficiency, and commercial performance.
• Provide ad-hoc analytical support for strategic projects, business cases, investment opportunities, and emerging commercial requirements across
• Collect, validate, structure, and analyse complex energy market datasets to identify trends, risks, opportunities, and actionable insights.
• Collaborate with commercial, investment, asset management, and strategy teams to ensure analyses support business objectives and commercial priorities.
• Apply analytical judgement to solve complex problems, evaluate alternative scenarios, and revoke practical solutions based on quantitative evidence.
• Support the continuous improvement of modelling standards, analytical