Senior Quantitative Modeller/Developer - Stochastic Simulations in Power Markets

About Baringa Baringa is a global consulting firm that partners with leaders to drive change and create value. With deep industry expertise, and enabled by advanced technology, the firm helps clients to deliver with greater confidence and certainty. With over 2,000 people across the UK, Europe, North America, Asia and Australia, the firm combines global insight with local understanding. The firm works across energy and resources, financial services, government and public sector, consumer products and retail, pharmaceuticals and life sciences, manufacturing, and technology, media and telecoms, with capabilities spanning strategy, transformation and operational excellence – all powered by advanced technology, data, AI and digital innovation. Clients value Baringa’s collaborative approach and the way its teams integrate seamlessly – all working with a shared understanding of what matters most. The firm is known for its kind, curious experts who listen closely and care deeply about client success as they help clients transform energy markets, modernise financial platforms, expand telecoms and digital networks through advanced data analytics, enable digital services in government, and unlock growth in consumer sectors. Certified as a Great Place to Work around the world, Baringa has been recognised by the Financial Times in 22 categories of its UK Leading Management Consultants rankings, and by Forbes for four consecutive years as one of the World’s Best Management Consulting Firms. Our Energy Products practice are looking for an experienced Senior Quantitative Modeller/Developer to join the team - Stochastic Simulations in Power Markets. The CORAL team within our Energy Products practice develops the modelling platform that underpins Baringa's market analysis, valuation, and optimisation capabilities across European energy markets. We build production-grade software used by our consultants, analysts, SaaS developers, and clients to model power markets, simulate market prices, optimise assets, and deliver long-term market insights. Our work spans statistical and stochastic models, optimisation, internal/external data, and AI-enabled tooling. We combine software engineering, quantitative methods, and energy market expertise to create scalable solutions that support both advisory engagements and productised offerings across Baringa globally. As our modelling capabilities continue to expand, we are looking for an experienced quantitative modeller to lead the development and evolution of our stochastic simulation framework and associated market modelling methodologies. What you will be doing Lead the design, development, calibration, and validation of Baringa's stochastic simulation models across power, gas, LNG, and other commodity markets. Develop advanced modelling methodologies including mean-reverting jump diffusion (MRJD), two-factor, and multi-factor stochastic models. Improve the representation of commodity price behaviour, volatility, market regimes, and structural market change within our modelling framework. Combine liquid horizon market data with Baringa's long-term fundamental market outlooks to create stochastic simulations that are consistent with our scenario-based simulations. Research and implement new quantitative approaches for modelling uncertainty, asset valuation, risk assessment, and market behaviour. Work closely with market modelling specialists, advisory teams, and clients to ensure models remain relevant, credible, and aligned with commercial decision-making. Partner with software engineers to ensure modelling methodologies are implemented as robust, maintainable, and scalable production software. Drive model calibration, validation, benchmarking, and ongoing performance monitoring. Communicate complex quantitative concepts clearly to technical, commercial, and executive audiences. Contribute to Baringa's thought leadership in quantitative energy market modelling and stochastic simulation. Your skills and experience Essential Significant experience developing and applying stochastic simulation models within power, gas, commodit