Quantitative Analyst – LNG

ConocoPhillips•Houston, TX

2d•Hybrid

About The Position

We are seeking a high-caliber Quantitative Analyst to join our team supporting global LNG trading, origination, structuring and portfolio optimization. The position sits within a centralized, multi-commodity quantitative analytics team and your work will directly influence trading decisions, deal structuring, portfolio value extraction, and risk management across cargo optimization, medium-term structures, and long-term SPAs. You will hold model ownership for the optimization and valuation engine at the core of our long-term LNG platform — accountable for optimization logic, constraint formulation, engine mathematics, model performance, and the commercial defensibility of the valuations it produces — and will partner directly with Structuring & Origination on high value, complex transactions. This role may require periodic international travel to our London and Singapore trading offices, up to 10% of the time.

Requirements

Legally authorized to work in the United States.
Master's degree or higher in Applied Mathematics, Operations Research, Financial Engineering, Statistics, Physics, Engineering, Computer Science, or a related quantitative discipline.
10 or more years of hands-on experience as a quantitative analyst in energy commodities or financial markets, with a demonstrated record of building and deploying production-grade valuation, optimization, or risk models.
Demonstrated command of optimization methods applied to commercial problems: mixed-integer linear programming, linear and network optimization, and stochastic or dynamic programming approaches.
Practical experience with commercial solvers (Gurobi, CPLEX, XPRESS, HiGHS) and modeling frameworks such as Pyomo.
Experience applying real options and derivatives pricing to physical optionality: spread options, swing and flexibility valuation, Black-76, and least-squares Monte Carlo or comparable dynamic programming methods.
Demonstrated experience building hedging analytics — Greeks computation, hedge construction, and hedge effectiveness measurement — for physical or structured commodity portfolios.
Experience with commodity price forecasting and quantitative modeling techniques, including simulation-based approaches used for valuation and risk management.
Advanced Python development skills with experience building production-quality analytical and quantitative modeling applications.
Knowledge of LNG market mechanics sufficient to encode them correctly: FOB and DES pricing, destination and diversion economics, quantity tolerances and make-up provisions, cancellation rights, shipping and chartering fundamentals, boil-off and voyage economics, and regasification and capacity arrangements.
Understanding of global LNG and gas market structure, including Atlantic and Pacific Basin trade flows, principal pricing hubs and indices, shipping economics, and portfolio optimization principles.
Experience with model validation, back-testing, calibration, and analytical governance frameworks.
Sufficient commercial fluency to work credibly with traders, originators, and structurers.
Proven ability to explain sophisticated quantitative work to commercial audiences, in writing and in person.
Demonstrated ability to work collaboratively, manage competing priorities, and deliver under commercial timelines without compromising model rigor.

Nice To Haves

Strong communication skills with the ability to explain complex analytical concepts to both technical and non-technical audiences.
Demonstrated ability to manage multiple priorities, collaborate across teams, and deliver high-quality results in a fast-paced commercial environment.
Experience valuing long-term LNG supply and offtake agreements, shipping portfolios, regasification capacity, storage assets, and structured LNG transactions.
Familiarity with Forward Freight Agreements (FFAs) and their use in commodity shipping markets to hedge future freight rates.
Experience pricing non-market risk exposures, including counterparty credit and operational risk factors.
Experience building dual-horizon optimization models —with appropriate constraint relaxation across horizons.
Familiarity with LNG shipping operations as optimization constraints.
Experience with large-scale, cloud-native compute architectures for quantitative workloads, including containerized solvers, asynchronous job queues, and distributed batch simulation.
Experience with enterprise data platforms such as Snowflake for managing scenario inputs, simulation outputs, and result persistence.
Familiarity with machine learning applied to energy markets, including freight and spot charter rate modeling, demand and price forecasting, or hybrid optimization and machine learning approaches.
Experience contributing to or maintaining a shared, multi-contributor quantitative library with enforced standards and code review.
Familiarity with model risk governance frameworks, independent model validation, and exposure or VaR quantification methodologies.
Exposure to ETRM or CTRM environments, deal capture, mark-to-market, and position management workflows.
Proficiency in C++ or C# alongside Python.

Responsibilities

Own and evolve the optimization logic, constraint formulation, and mathematical engine underpinning our LNG portfolio valuation platform.
Support deal structuring on complex transactions, providing independent quantitative challenge on methodology, assumptions.
Extend the platform to accommodate new contract types, pricing structures, and market features as the origination pipeline evolves, including structures the current model cannot yet represent.
Manage solver performance and runtime, model scalability, and the compute economics of running large batches of parallel scenario and optimization cases.
Lead model validation and assurance activity: back-testing, stress testing, sensitivity analysis, synthetic and edge-case test construction, benchmarking against accepted external references, and reconciliation of model output against independent calculation.
Develop pricing frameworks for optionality that standard valuation does not adequately capture — spread options, swing and flexibility valuation, compound and embedded structures, and non-standard indexation.
Deliver model outputs that stand up to scrutiny: intrinsic and extrinsic value decomposition, profit attribution by source, hedging analytics, and stochastic cash flow distributions.
Maintain rigorous model documentation, automated test coverage, release notes, versioned assumptions, and calculation lineage sufficient to withstand internal audit and independent peer review.
Collaborate with Commercial IT, data engineering, and data science teams on productionization, data pipeline integrity, and release validation — retaining full ownership of the underlying mathematics.
Contribute reusable components — curve handling, calendars, optimization building blocks, scenario frameworks — back into the shared multi-commodity quantitative library, and help establish the modeling standards and governance practices that library will run on.
Participate in commercial and governance discussions, clearly communicating valuation methodology, optionality drivers, sensitivities, and portfolio impacts to technical and non-technical audiences alike.

Benefits

Competitive base salary commensurate with experience, plus performance-based bonus.
Model ownership of an institutionally significant LNG valuation and optimization platform, with a defined enhancement roadmap and senior leadership visibility rather than a legacy system in maintenance mode.
Direct line of sight from your models to multi-billion-dollar commercial decisions.
A centralized quantitative team being built and scaled deliberately, with strong institutional backing for capability development, and reach across crude, natural gas, power, LNG, and NGLs beyond your primary LNG alignment.
Close partnership with traders, originators, structurers, market analysts, and risk management across Houston, London, and Singapore.
Comprehensive benefits including medical, dental and vision coverage, a company-funded pension plan, a 401(k) with company match, and relocation support where applicable.
Medical, dental, vision, mental health support, and wellness programs.
Competitive base pay, annual performance bonuses, and retirement savings plans.
Paid time off, paid parental leave, and family support resources.
Access to training, mentoring, and internal career mobility tools.
Peer-nominated awards, inclusive culture, and employee resource groups.