Future Talent Pipeline - Commercial Data Scientist

Phillips 66 • Houston, TX

8d

About The Position

Are you interested in joining Phillips 66 but don’t see a current opening that matches your skills? We’d love to connect! This posting is part of our Talent Pipeline Program for future Commercial Data Scientist opportunities.

We are actively building a network of talented professionals we’d like to consider for upcoming positions. If a current Commercial Data Scientist opening doesn’t align with your career goals or preferred location, we encourage you to apply to this "Future Talent Pipeline" position instead and stay connected for upcoming roles.  

The Commercial Data Scientist is embedded in a collaborative, entrepreneurial environment, working alongside experienced data scientists, software engineers, and commercial teams. Expect to tackle complex, high-impact problems, contribute to the energy transition, and see your work influence business decisions at scale.

Requirements

• Bachelors degree (or equivalent) in Computer Science, Data Science, Machine Learning, or a related field; Ph.D. is a plus
• 3+ years of industry experience developing and deploying machine learning models and advanced analytics solutions
• Advanced proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn); experience with Databricks, Spark, and Azure cloud services; familiarity with containerization (Docker) is a plus
• Advanced coursework in math, statistics, and machine learning
• Legally authorized to work in the posting country

Nice To Haves

• Thrives in ambiguous, high-volume data environments, accurately defining key elements and encouraging innovative analysis.
• Creates new and better ways for the organization to succeed, offering original ideas and enhancing others’ creative solutions.
• See’s ahead to future possibilities, translating trends and insights into breakthrough strategies for the business.
• Experience in the energy or commodities trading industry, with knowledge of financial markets and trading concepts
• Proven ability to integrate machine learning systems into interactive dashboards (e.g., Dash, Streamlit) and present use cases to non-technical colleagues
• Resourceful, adaptable, and motivated to make an impact in a dynamic, fast-growing team
• Demonstrable attention to detail and commitment to quality
• Expertise in exploring and extracting insights from large multi-source data sets
• Strong problem-solving skills and ability to work independently and collaboratively
• Strong foundations in statistics, time series modeling, and econometrics
• Excellent communication skills, able to explain complex technical concepts to non-technical stakeholders

Responsibilities

• Analyze large, complex datasets to uncover insights, patterns, and trends that drive business strategy and operational improvements
• Partner with trading desks, commercial teams, and IT ML Engineers to implement predictive analytics projects and deploy models using MLOps best practices (CI/CD, MLflow, monitoring) on Databricks-on-Azure tech stack
• Design, build, and integrate data science solutions into existing systems and platforms for seamless user experiences
• Perform complex statistical analysis, data mining, and visualization to enable data-driven decision-making
• Contribute to reporting strategies, translating analytical findings into actionable recommendations for stakeholders
• Share knowledge and build data science expertise within the business through mentoring and collaboration
• Actively participate in code reviews, experiment design, and tooling decisions to drive team quality and velocity

Benefits

• Annual Variable Cash Incentive Program (VCIP) bonus
• 8% 401k company match
• Cash Balance Account pension
• Medical, Dental, and Vision benefits with an annual company contribution to a Health Savings Account for employees on HDHP
• Total well-being programs and incentives, including Employee Assistance Plan, well-being reimbursement, and backup family care services

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees