Quantitative Risk Analyst
On-siteSpring, Texas, United States
Job Summary
Quantitative Risk Analyst to develop, govern, and explain risk models across physical and financial natural gas, LNG, and power portfolios within a commodity trading business. Responsibilities include building valuation/exposure models for storage, transport, tolling, and optionality; supporting mark-to-market, forward curves, volatility surfaces, scenario analysis, and P&L attribution; strengthening risk-framework governance and documentation; creating scalable analytics in Python and integrating with ETRM/CTRM systems (Endur, Allegro, ZEMA). Key skills include advanced Python (pandas, NumPy, SciPy), data visualization, MC simulation, time-series analysis, and ability to communicate quantitative results to traders, risk managers, and senior leadership. Education requirements include a Bachelor's degree in a quantitative field; a Master’s or PhD is preferred. The role emphasizes cross-commodity valuation, risk-control orientation, and collaboration with trading, structuring, origination, risk, technology, and finance teams. Location is Finance, TX (Spring) with on-site expectations.
Required Qualifications
- Bachelor's degree in a quantitative discipline required (e.g., Mathematics, Statistics, Physics, Engineering, Computer Science, Econometrics, Finance, Applied Economics)
- Experience in quantitative risk, quantitative analytics, structuring, valuation, or model development in commodity trading, energy trading, or related environments
- Demonstrated ability to model optionality of complex/dynamic systems
- Strong programming skills in Python; familiarity with SQL and one or more of C#, C++, VBA
- Ability to communicate complex model outputs to traders, risk managers, and executives
- Experience with risk metrics (VaR, ES, stress testing) and governance/documentation requirements
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