Director, Quantitative Analysis

Job Summary

We are seeking a senior quantitative professional to serve as the Lead Quantitative Analyst and working supervisor for ConocoPhillips' commercial quant function. This is a high-impact, player-coach role — you will be a hands-on quantitative contributor as much as a team leader, personally driving model development and owning the mathematical processes alongside the analysts you lead.

Position Overview

• Technical Leadership & Model Development
  Own the mathematical design and intellectual core of ConocoPhillips' multi-commodity quantitative library — a centralized framework covering valuation, pricing, simulation, optimization, and risk across crude, natural gas, LNG, power, and NGLs.

• Design and maintain pricing models for vanilla and exotic derivatives, physical embedded optionality (e.g., storage, transport, swing, tolling, SPAs with flex provisions), and structured commodity products.

• Develop and own stochastic price process models — including mean-reverting, GBM, jump-diffusion, and multi-factor models — calibrated to forward curves, volatility surfaces, and historical correlations.

• Own option pricing frameworks (Black-76, spread options, real options, Monte Carlo, Longstaff-Schwartz, Least-Squares Monte Carlo) with rigorous delta/Greeks computation and hedging analytics for use by traders, originators, and risk managers.

• Build and maintain forward curve construction and calibration routines using spline, bootstrap, and parametric methods, integrating live market data from ICE, Platts, Bloomberg, and internal sources.

• Lead model validation efforts including back-testing, stress testing, sensitivity analysis.

• Design scalable simulation frameworks suitable for large-scale Monte Carlo workloads, scenario analysis, and optimization loops across multi-commodity portfolios.

• Quant Library & Platform
  Own the mathematical framework and ongoing evolution of a centralized, reusable quantitative library — ensuring models are rigorously documented, peer-reviewed, and grounded in sound, defensible methodology.

• Establish and enforce modeling standards, validation protocols, and governance practices across the quant library — setting the bar for mathematical rigor, assumption transparency, and auditability.

• Partner with Commercial IT to ensure quant model outputs are accessible and deployable within commercial workflows, while retaining full ownership of the underlying mathematics and model logic.

• Ensure all models carry full audit trails, documented assumptions, version-controlled runs, and calculation methodologies defensible for senior leadership and risk governance review.

• Team Leadership & Mentorship
  Lead and mentor a team of quantitative analysts across commodity lines — conducting code reviews, model reviews, and technical coaching to elevate team capability and output quality.

• Define and steward the quant team's analytical roadmap in close coordination with commercial leadership, traders, market analysts, and risk management.

• Allocate team resources across competing priorities — balancing long-term library development with time-sensitive deal support and ad hoc analytical requests from desks.

• Recruit and develop quant talent; establish clear performance standards, technical benchmarks, and career development frameworks for the team.

• Serve as the primary interface between the quant team and commercial stakeholders — translating complex model outputs into decision-ready insights for traders, originators, and senior leadership.

• Deal Support & Commercial Integration
  Provide direct quant support on high-value commercial transactions — including deal valuation, structuring analysis, bid/offer support, and scenario analysis.

• Partner with originators, traders, market analysts and risk managers to ensure quant models are calibrated to current market conditions and reflect deal-specific terms with precision.

• Support portfolio-level analysis including value attribution, extrinsic value capture opportunities, hedge effectiveness testing, and optimal hedging strategy design.

Required Qualifications

• 15+ years of hands-on experience as a quantitative analyst or quant researcher in energy commodities or financial markets, with a demonstrable track record of building production-grade pricing and risk models.
• Deep expertise across multiple commodity classes — prior experience spanning at least two of: crude, natural gas, power, LNG, or NGLs is required; coverage across all five is strongly preferred.
• Expert-level proficiency in stochastic process modeling, derivatives pricing (Black-76, Monte Carlo, LSMC, spread options), volatility surface calibration, and real options valuation.
• Advanced programming skills in Python (required); proficiency in C++ or C# is a strong plus.
• Must be capable of translating rigorous mathematical frameworks into well-structured, maintainable code — not just one-off analytical scripts.
• Strong understanding of energy market structure, physical and financial commodity contracts, and the embedded optionality in storage, transportation, and long-term offtake agreements.
• Prior experience in a player-coach or technical lead capacity — managing or mentoring analysts while maintaining active, hands-on model development.
• Exceptional mathematical foundation: stochastic calculus, numerical methods, linear algebra, and optimization.
• Master’s degree (required) in Mathematics, Physics, Financial Engineering, Computer Science, Engineering, or a closely related quantitative field. PhD strongly preferred.

Preferred Qualifications

• Familiarity with VaR/CVaR model design, Greeks-based hedging frameworks, and model risk governance standards.
• Experience integrating quant models with enterprise data platforms (Snowflake, Azure Databricks) and deploying model outputs via REST APIs or interactive dashboards (Power BI, Dash, Streamlit).
• Knowledge of optimization methods (LP, MILP, Stochastic Optimization, ADP) as applied to portfolio scheduling, capacity allocation, or dispatch modeling.
• Experience working directly on a commodity trading floor or in close partnership with trading desks in a deal-support capacity.
• FRM, CFA, or equivalent professional designation is a plus.