Sr. Advisor III, Commercial Data Scientist

Phillips 66 & YOU - Together we can fuel the future The Sr. Advisor III, Commercial Data Scientist serves as a high-autonomy technical subject matter expert for advanced analytics and machine learning across the Commercial organization. Operating as the senior technical partner to the Chief Data Scientist, the Commercial Data Scientist will independently own desk relationships, deliver high value work, and set the standard for the team as the founding hire for commercial data scientist capability embedded with the trading desks. The Commercial Data Scientist will partner directly with traders and market analysts, turn messy market and operational data into decision-quality signals, and establish the validated data products and production workflows that let the broader team scale. The desks have concrete opportunities in ship tracking, supply and demand modeling, outage analytics, arbitrage, and scenario analysis, plus a cross-desk need to stop rebuilding the same work. Because no model is trustworthy without robust upstream data, this hire will both deliver high-value trading use cases and help build the data science operating model on governed, business-ready data. What You'll Do • Partner directly with traders, strategists, market analysts, and Commercial leaders to frame high-value problems, identify opportunities, and integrate validated analytical insights into business and trading decisions. • Lead end-to-end data science initiatives across forecasting, scenario analysis, optimization, anomaly detection, signal generation, and other advanced analytics use cases. • Identify, assess, and enhance internal, external, and alternative data sources for quality, coverage, timeliness, and commercial relevance; establish trusted, business-ready data products. • Translate desk-specific analyses and solutions into reusable methods, modeling patterns, and tools that can scale across commodities, markets, and Commercial teams. • Develop production-quality code and partner with data engineering, ML engineering, and software development teams on deployment, monitoring, CI/CD, MLflow, and durable MLOps workflows. • Set technical direction and reusable foundations for the team, participate in tooling and architecture decisions, and mentor data scientists and other technical team members without relying on formal management authority. • Communicate complex technical concepts, model results, uncertainty, and recommendations clearly to technical peers, commercial stakeholders, and senior leadership; develop or integrate analytical solutions into dashboards and existing platforms to improve decision speed. What You'll Bring – Required • Legally authorized to work in the United States • Master’s degree or higher in Computer Science, Data Science, Machine Learning, Statistics, Applied Mathematics, Economics, Engineering, Physics, or a related quantitative field • 6 or more years of industry experience developing and deploying advanced analytics and machine learning solutions, including a track record of independently owning ambiguous problems from hypothesis through business adoption • Strong Python data science skills and production-quality coding experience • Strong mathematical and statistical foundations, including inference, time-series modeling, econometrics, optimization, and rigorous model evaluation • Demonstrated ability to extract insights from large, complex, multi-source datasets and translate analytical findings into actionable commercial recommendations • Excellent communication and stakeholder management skills, with the ability to influence technical peers, commercial partners, and senior leaders What Makes You Stand Out – Preferred • PhD in Computer Science, Data Science, Machine Learning, Statistics, Applied Mathematics, Economics, Engineering, Physics, or a related quantitative field • Experience in energy, commodities, trading, financial markets, or another decision-intensive commercial environment, with an understanding of price formation, market structure, and risk • Depth in time-series analysis, forecasting, optimization, geospatial data, anomaly detection, or applied machine learning used in live business decisions • Experience shaping shared research, modeling, or data-product infrastructure rather than delivering only one-off analyses • Experience working across front office, risk, compliance, IT, Digital, and other cross-functional teams to deliver durable business outcomes Compensation Range This position has a base salary range of $180,900 - $221,100. This role is eligible to participate in the company’s commercial bonus program, offering the opportunity to earn additional compensation based on business and individual performance, in accordance with program guidelines. At Phillips 66, we are committed to pay transparency and competitive, equitable compensation. Each role is assigned a salary grade with a defined pay range, benchmarked against industry peers. Where a candidate offer falls within the posted range depends on the candidate's experience, skills, and alignment with the role’s requirements. Offers are made to ensure internal equity and market competitiveness. Our compensation programs are designed to reward performance and support career growth. The Commercial organization works to effectively leverage assets and market knowledge to create additional value within the risk parameters of the Company. We do this by maximizing general interest profitability, enhancing return on capital employed by successfully partnering with the Refining, Transportation and Marketing functions to ensure Value Chain Integration. Our truck and rail fleets support our feedstock and distribution operations. Rail movements are provided via a fleet of more than 10,000 owned and leased rail cars. Truck movements are provided through numerous third-party trucking companies, as well as through our 100 percent-owned subsidiary, Sentinel Transportation LLC. Total Rew