ConocoPhillips

ConocoPhillips

Quantitative Analyst – LNG

Houston, TX, USA

Sponsorship not specifiedDetected 2 hours ago
PythonC++C#SnowflakeMachine LearningData EngineeringData ScienceStatisticsForecastingValuationAuditingLoad TestingResearchLeadershipCommunicationCollaborationMentoringInternal AuditPipeline Integrity

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odds of building a lasting career here

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Cap-exempt (no lottery)0
Sponsors this role65
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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Files H-1B transfers

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About the role

  • We are seeking a high-caliber Quantitative Analyst to join our team supporting global LNG trading, origination, structuring and portfolio optimization.
  • This role may require periodic international travel to our London and Singapore trading offices, up to 10% of the time.

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.
  • Manage solver performance and runtime, model scalability, and the compute economics of running large batches of parallel scenario and optimization cases.
  • 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.
  • 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.
  • Partners Collaboratively
  • Builds positive relationships based on trust and seeks collaboration across organizational boundaries to achieve goals.
  • 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.
  • Deliver model outputs that stand up to scrutiny: intrinsic and extrinsic value decomposition, profit attribution by source, hedging analytics, and stochastic cash flow distributions.

Requirements

  • Master's degree or higher in Applied Mathematics, Operations Research, Financial Engineering, Statistics, Physics, Engineering, Computer Science, or a related quantitative discipline.
  • 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.
  • Experience with commodity price forecasting and quantitative modeling techniques, including simulation-based approaches used for valuation and risk management.
  • Experience with model validation, back-testing, calibration, and analytical governance frameworks.
  • Proven ability to explain sophisticated quantitative work to commercial audiences, in writing and in person.

Nice to have

  • Strong communication skills with the ability to explain complex analytical concepts to both technical and non-technical audiences.
  • 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.
  • 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.
  • Experience contributing to or maintaining a shared, multi-contributor quantitative library with enforced standards and code review.

Compensation

  • Competitive base salary commensurate with experience, plus performance-based bonus.

Benefits

  • Competitive base salary commensurate with experience, plus performance-based bonus.
  • Comprehensive benefits including medical, dental and vision coverage, a company-funded pension plan, a 401(k) with company match, and relocation support where applicable.
  • Benefits Overview
  • ConocoPhillips offers a competitive and comprehensive benefits package designed to support your well-being and career growth:
  • Taking Care of Your Health & Wellness: Medical, dental, vision, mental health support, and wellness programs.
  • Supporting and Building Financial Security: Competitive base pay, annual performance bonuses, and retirement savings plans.
  • Maintain rigorous model documentation, automated test coverage, release notes, versioned assumptions, and calculation lineage sufficient to withstand internal audit and independent peer review.

Company info

  • We are one of the world's largest independent exploration and production companies, based on proved reserves and production of liquids and natural gas. With operations and activities in 13 countries, we explore for, develop, and produce crude oil and natural gas globally. We are challenged with an important job to safely find and deliver energy to the world. Our employees are critical to our success, and with them we power civilization.
  • We're grounded by our SPIRIT Values - safety, people, integrity, responsibility, innovation, and teamwork. These values position us to deliver strong performance in a dynamic business - but not at all costs. We believe it's not just what we do - it's how we do it - that sets us apart.
  • Fostering an Inclusive Work Environment
  • To deliver superior performance, we create an environment that respects the contributions and differences of every individual. Wherever possible, we use these differences to drive competitive business advantage, personal growth and, ultimately, create business success.
  • We are one of the world's largest independent exploration and production companies, based on proved reserves and production of liquids and natural gas.
  • With operations and activities in 13 countries, we explore for, develop, and produce crude oil and natural gas globally.
  • We are challenged with an important job to safely find and deliver energy to the world.
  • Our employees are critical to our success, and with them we power civilization.
  • We're grounded by our SPIRIT Values - safety, people, integrity, responsibility, innovation, and teamwork.
  • These values position us to deliver strong performance in a dynamic business - but not at all costs.
  • We believe it's not just what we do - it's how we do it - that sets us apart.
  • To deliver superior performance, we create an environment that respects the contributions and differences of every individual.
  • Wherever possible, we use these differences to drive competitive business advantage, personal growth and, ultimately, create business success.

Equal opportunity

  • In the US, ConocoPhillips is an Equal Opportunity Employer.
  • All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, veteran status, gender identity or expression, genetic information, or any other legally protected status.

Visa & Work Authorization

  • ConocoPhillips' sponsorship for employment authorization in the U.S. is NOT available for this position.
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This listing is sourced directly from ConocoPhillips's careers page and normalized into a canonical job model.