Summary: Repsol is seeking a Quantitative Analyst to develop and maintain sophisticated models for valuing and simulating optionality in energy contracts. Highlights: 1. Develop and maintain sophisticated quantitative models for energy contracts 2. Collaborate with traders and risk managers to translate insights into strategies 3. Opportunity to grow professionally and develop your career At Repsol, we are committed to equality and do not request personal information. We believe that diversity contributes to innovative ideas and provides added value that enables us to benefit from mutual learning and perform our best work. Here, what counts is your experience and your ability to create value. We offer you the opportunity to grow professionally, develop your career with challenging projects and collaborate with talented people worldwide. As a company committed to diversity and inclusion, we encourage all professionals who meet the job description requirements to apply. Key information Team: D. CONTROL \& ADMINISTRATION WGT Location: Madrid, Spain Experience level: 5\-7 years Job type: hybrid Requirements: english C1 level \+ Bachelor's and Master's Degree Main tasks* Optionality Modeling: Develop and maintain sophisticated quantitative models to value and simulate optionality in LNG, gas, and power contracts, including flexibilities in delivery, pricing, and volume adjustments. Incorporate stochastic processes, Monte Carlo simulations, and real options analysis to capture uncertainties in market dynamics. * Asset Integration: Analyze and model physical assets such as pipelines, shipping routes, storage caverns, and terminal slots, assessing their impact on portfolio optionality and operational flexibility. * Interconnections and Cross\-Sector Modeling: Build integrated models that link energy portfolios with refinery operations, petrochemical feedstocks, and cogeneration systems, optimizing for energy efficiency, cost minimization, and revenue maximization across interconnected value chains. * Hedging Strategy Development: Design, implement, and backtest hedging programs using derivatives (futures, options, swaps) to mitigate price, volume, and basis risks in a multi\-commodity setting, ensuring alignment with overall portfolio objectives. * Portfolio Optimization: Create optimization frameworks (e.g., linear/non\-linear programming, dynamic programming) for global cross\-commodity portfolios, balancing supply chain constraints, market arbitrage opportunities, and regulatory compliance. * Risk Assessment and Scenario Analysis: Perform stress testing, sensitivity analysis, and scenario modeling to evaluate portfolio exposures under various market conditions, including geopolitical events, weather impacts, and supply disruptions. * Collaboration and Reporting: Work closely with traders, risk managers, operations teams, and senior stakeholders to translate quantitative insights into actionable strategies. Prepare detailed reports, visualizations, and presentations to communicate findings and recommendations. * Innovation and Research: Stay abreast of emerging quantitative methods, machine learning applications, and industry trends in energy modeling; contribute to the enhancement of internal tools and methodologies. What we offer* Permanent contract * Bonus according to objectives * Medical insurance * Contribution to pension plan * Digital disconnection * Conciliation measures * Legal advice * Employee support services You will fit the position if:* Education: Advanced degree (Master's or PhD) in Quantitative Finance, Applied Mathematics, Physics, Engineering, Operations Research, or a related field. * Experience: Minimum of 5\-7 years in quantitative analysis within energy/commodities trading, structuring, or risk management, with proven expertise in modeling optionality for physical portfolios. Experience in LNG, natural gas, power markets, or related sectors is essential; prior work with refinery/petrochemical/cogeneration integrations is highly desirable. * Technical Proficiency: + Strong programming skills in Python, R, MATLAB, or C\+\+, with experience in libraries such as NumPy, SciPy, Pandas, or optimization tools like Gurobi/CPLEX. + Expertise in stochastic calculus, time\-series analysis, volatility modeling, and optimization algorithms. + Familiarity with energy\-specific software (e.g., for dispatch optimization or Monte Carlo engines) and data sources (e.g., Bloomberg, Refinitiv). * Market Knowledge: Deep understanding of global energy markets, including LNG spot and term contracts, gas hub pricing, power grid dynamics, and cross\-commodity correlations (e.g., gas\-oil spreads, power\-heat linkages). \#LI\-CG1