Apply on Employer Site

Phillips 66 · 1 day ago

Commercial Data Scientist

Houston, TX

Full-time

Onsite

Mid Level

$198K/yr - $242K/yr

3+ years exp

Phillips 66 is a global leader in the energy sector, seeking a Commercial Data Scientist to drive real-world impact across various markets. The role involves analyzing complex datasets, implementing predictive analytics projects, and contributing to the energy transition by influencing business decisions at scale.

EnergyLogisticsManufacturing

Comp. & Benefits

No H1B

U.S. Citizen Only

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

Qualification

Machine LearningPythonData AnalysisDatabricksAzureStatistical AnalysisCommunication SkillsProblem-SolvingAttention to Detail

Required

Master's 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

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

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

Advanced coursework in math, statistics, and machine learning

Demonstrable attention to detail and commitment to quality

Legally authorized to work in the posting country

Preferred

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