Quantitative Analyst

Description

Enlight Renewable Energy is seeking a skilled Quantitative Analyst to join its team and support the analysis and optimisation of renewable energy, battery energy storage (BESS), and hybrid power projects. In this role, you will design and maintain advanced quantitative models to support revenue forecasting, risk management, and hedging strategies, working closely with Trading, Finance, and Development teams across the organization.

Location: Europe or Israel. Preference will be given to candidates with experience in European energy markets; however, candidates based in Israel with strong quantitative capabilities are also encouraged to apply.

Responsibilities

• Revenue Modelling: Develop, calibrate, and maintain an in-house revenue modelling tool for renewable, BESS, and hybrid projects using Python or R.
• Risk Analytics: Design and manage an in-house Value-at-Risk (VaR) framework for the operational portfolio, leveraging Monte Carlo simulations.
• Derivative Pricing: Build and maintain pricing models for financial derivatives to support hedging strategies for merchant positions (e.g., tolls, floors, virtual arbitrage).
• Cross-functional Collaboration: Work closely with Trading, Finance, and Development teams to ensure models are robust, transparent, and aligned with market best practices.
• Documentation & Knowledge Sharing: Document methodologies, assumptions, and model structures, and support internal training and adoption.

Requirements

• At least 3 years of experience in data science, quantitative analysis, or energy analytics, preferably within the energy trading or renewables sector.
• Proficiency in Python or R, with hands-on experience in modelling, statistical analysis, and data visualisation.
• Strong understanding of European electricity markets (preferred).
• Experience with financial derivatives, stochastic modelling, and/or Monte Carlo simulations (preferred).
• Academic degree in a quantitative field such as Applied Mathematics, Statistics, Engineering, Physics, Computer Science, or a related discipline. A Master’s degree or PhD is an advantage.
• Strong communication skills, with the ability to translate complex quantitative models into clear and actionable business insights.