Commodities Quantitative Developer (Greenwich)
SaltHill Group
A global energy trading merchant seeks an experienced quantitative professional to join a commercially oriented power and gas Strats team. The Quantitative Developer supports front-office power and natural gas trading teams by developing and implementing quantitative models, pricing tools, and risk management solutions. This position works directly with the originators, traders, quants, and customers who price derivatives and structure complex, competitive deals and products.
The ideal candidate combines strong quantitative and mathematical finance skills with hands-on software development experience and a solid understanding of energy and commodity markets. The role requires the ability to translate complex mathematical and financial problems into practical, well-documented, and reliable technology solutions.
Key responsibilities include:
- Quantitative Model Development: Develop, enhance, document, and test pricing models and quantitative libraries used to value power and natural gas products, derivatives, and structured commodity transactions.
- Trading Analytics and Tools: Build and maintain pricing applications, analytical tools, and risk reports to support traders, originators, middle-office professionals, and risk management teams.
- Risk Management Systems: Enhance quantitative risk systems and collaborate with IT to implement new functionality, accommodate complex transactions, and improve existing reporting capabilities.
- Model Calibration and Validation: Calibrate pricing models using observable market data and historical price information, working closely with traders to ensure models reflect current market conditions and trading requirements.
- Risk Measurement: Develop and implement quantitative methodologies for measuring and analyzing market risk, valuation, and credit exposure associated with long-term contracts and structured commodity deals.
- Complex Transaction Support: Participate in the quantitative analysis, pricing, and structuring of complex power and natural gas transactions, translating commercial requirements into robust analytical solutions.
- Software Engineering: Write efficient, maintainable, and well-tested code; improve the performance, reliability, and usability of quantitative applications and libraries.
- Cross-Functional Collaboration: Partner with traders, quantitative strategists, risk managers, and technology teams to identify analytical needs, deliver solutions, and support the continued development of the trading platform.
The ideal candidate has a background in commodities and energy (power, gas, crude oil, refined products) and can understand or learn the math behind structured deals, build/optimize rigorous quantitative models, write code in a robust framework (production-style way), and organize the interface with systems/data/pricing libraries.
Educational and professional requirements include:
- An advanced degree (Ph.D. or master’s) in a quantitative field (hard sciences required - mathematics, engineering, physics, computer science, etc.).
- Strong numerical and analytical skills
- Experience with mathematical finance, derivatives, option pricing, and stochastic calculus
- Strong understanding of embedded optionality and drivers
- Minimum 2-7 years of professional experience in a power or gas quantitative role in an energy trading firm, investment bank, utility, IPP, or energy consulting
- Experience with pricing model development and back-testing. Writing and building pricing or valuation models and libraries in a production environment, including back-testing and risk integration
- Experience pricing and structuring complex power and/or gas transactions (exotic options, bespoke structures, etc.) desired
- Experience in Python and an object-oriented language (C#, C++, Java, or similar) required
- Good communication skills
- Ability to work in a fast-paced environment
This position can be located in Greenwich, CT or Houston, TX. This position follows a hybrid work schedule, combining in-office and remote work.
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