Rodney Murray

Data Scientist/Engineer

Senior Data Scientist with 11+ years of experience and a petroleum engineering background, skilled at architecting scalable data platforms (Snowflake, dbt, AWS) and deploying ML/AI solutions that drive multimillion-dollar impacts. Holds a degree in Chemical Engineering from the University of Wyoming and a Master of Applied Statistics from Colorado State University.

Experiences

Senior Data Scientist

ConocoPhillips

2020 - Present | Anchorage, AK

Lead data science initiatives across multiple functions to optimize oilfield operations, production, and data infrastructure using advanced analytics, machine learning, and cloud technologies.

• Increased annual revenue by >$9 million through utilization of reinforcement learning with a Python based environment for waterflood optimization.
• Added >$6 million of annual revenue by deploying a neural network combined with a genetic algorithm for optimization of production wells. Developed a robust deployment pipeline integrating the AWS Sagemaker deployment and process control environments for seamless operational use.
• 30x increase in speed of production rate forecasting while maintaining forecast accuracy enabled engineers to analyze access results in near real-time for field analysis. This was accomplished through the development of a deep learning model deployed via Ray for distributed computing and utilizing AWS S3 and Athena for data storage and querying.
• Reduced code volume and complexity by 30% and developed robust CI/CD pipelines for 5 key projects by refactoring Python-based data pipelines to leverage Snowflake and dbt. The effort streamlined processes and established a culture of technical excellence in the team through targeted mentorship and upskilling.
• Projected 40-60 hours/month time savings through implementation of simplified well performance workflows built in SvelteKit and JavaScript.
• Identified and piloted dbt Cloud for Snowflake data transformations, driving corporate approval to standardize dbt workflows with GitHub for version control and robust CI/CD pipelines.

Voidage Management Coordinator

ConocoPhillips

2019 - 2020 | Anchorage, AK

Coordinated waterflood and gas injection operations, leveraging analytics and optimization to maximize production and efficiency across assets.

• >$5 million annual increase in revenue from operational changes. Accomplished by collaborating in a multidisciplinary team to deploy a deep learning network coupled with a genetic algorithm for production optimization analysis by engineers. Published in SPE-201760-MS.
• Implemented custom optimization algorithms to allocate resources for water alternating gas injection conversions leading to improved production and reduced time spent by >4 hrs./week.
• Shared data analysis processes and BI tools for analysis of streamlines simulation results with two international business units resulting in adoption in Norwegian assets.
• Provide data-driven insights to engineers for injector performance through the maintenance and analysis of results from a reservoir simulation model.

Reservoir Engineer

ConocoPhillips

2014 - 2019 | Anchorage, AK

Provided reservoir engineering support for waterflood optimization, project economics, and simulation studies to drive value in mature assets.

• Evaluated economics and received approval for expense projects totaling >$2 million NPV.
• Reduced time to insight of >1000 wells via utilization of reservoir simulation on a HPC cluster.
• Led pattern health reviews resulting in decisions leading to a > $6 million annual revenue increase.

Education

• Master of Applied Statistics

  Colorado State University • GPA: 4.0 • 08/2021 - 05/2024

• B.S. Chemical Engineering

  University of Wyoming • GPA: 3.74 • 08/2010 - 05/2014

Skills

• AWS (Sagemaker, Athena, S3)

  Integrated S3, Athena, and Sagemaker to build scalable data pipelines, deploy ML models, and enable real-time analytics for oilfield operations.

• CI/CD

  Developed and maintained CI/CD pipelines for automated testing and deployment of data science and analytics projects, ensuring rapid and reliable delivery.

• dbt

  Designed and managed data transformation workflows in dbt for Snowflake, standardizing analytics engineering and enabling robust version control and CI/CD processes with GitHub.

• Distributed Computing

  Leveraged Ray to accelerate model training and inference, reducing time to insight for large datasets.

• Docker

  Containerized data science applications for consistent development, testing, and deployment across environments.

• Python

  Developed machine learning and Bayesian models for production optimization and forecasting using PyMC, scikit-learn, and Keras/TensorFlow.

• Snowflake

  Architected and optimized cloud data warehouses in Snowflake to support analytics, reporting, and machine learning workflows.

• SQL

  Designed and executed complex SQL queries for data extraction, transformation, and analysis across large-scale datasets.

• SvelteKit

  Built interactive web applications and internal tools for engineering workflows using SvelteKit and JavaScript.

• Git

  Used Git, GitHub, and GitLab for version control, collaboration, and CI/CD integration in analytics and engineering projects.

• Terraform

  Provisioned and managed cloud infrastructure as code using Terraform for reproducible and scalable deployments of ML infrastructure.