D&C Machine Learning Engineer And Data Scientist

D&C MachineLearning Engineer and Data Scientist

• 00032367

Oxy is an international energy company with assets primarily in the United States, the Middle East and North Africa. We are one of the largest oil and gas producers in the U.S., including a leading producer in the Permian and DJ basins, and offshore Gulf of Mexico. Our midstream and marketing segment provides flow assurance and maximizes the value of our oil and gas. Our chemical subsidiary OxyChem manufactures the building blocks for life-enhancing products. Our Oxy Low Carbon Ventures subsidiary is advancing leading-edge technologies and business solutions that economically grow our business while reducing emissions. We are committed to using our global leadership in carbon management to advance a lower-carbon world. Visit oxy.com for more information.

We are looking for an experienced and motivated individual to fill the position of Drilling and Completions Machine Learning Engineer and Data Scientist in our Worldwide Drilling and Completions organization based in Houston, Texas.

This role is responsible for advancing the drilling and completions analytics and digital transformation goals as part our strategic vision.

Essential Duties:

• Interface daily with multiple stakeholders, understanding needs, and creating solutions to address operational pain points.

• D&C technical SME for data analytics and Machine Learning development, interfacing with other OXY IT and practitioners.

• Development and deployment of a data repository for Drilling and Completions that allows the Ingestion of several structured and unstructured data sources.

• Assist DLT in data strategy development.

• Edget Iot algorithm development and deployment.

• Support Research and Development for algorithm development and testing.

Qualifications

• Bachelor of Science degree in Petroleum Engineering or related engineering field, Master’s Degree is preferred
• Minimum of 8 years of relevant experience
• Minimum 2 years unconventional well drilling engineering preferred.
• Minimum 3 years in lead role developing analytics or automation systems for unconventional drilling.
• Relevant computer science education/certifications strongly preferred.
• Knowledgeable of all aspects of drilling engineering, well design, geology and geophysics for drilling, logistics, and contractor management for drilling operations
• Strong petroleum and computer and Data science background
• Relevant experience in:
• Cloud development. AWS (IoT Core, IoT SiteWise, IoT Greengrass, SageMaker, Batch, Lambda, Kinesis, DynamoDB), Azure (Databricks, Synapse, Event Hubs, Azure ML)
• Programming Languages: Python, SQL, Bash Shell Operating Systems: Linux/Ubuntu
• Distributed Systems: Apache Spark, Airflow, etc.
• Deep Learning Frameworks: PyTorch, Tensorflow, etc
• DevOps: CI/CD, Terraform, CloudFormation, Git, etc
• Strong experience in Research and Development
• Strong presentation skills
• Strong skills working independently and in small teams.
• Understanding of physics-based drilling engineering models
• In-depth knowledge of electronic drilling data systems and rig control systems
• Ability to program Python, VBA, or equivalent language
• Ability to develop Spotfire or Power BI dashboards
• Understanding of relational and non-relational data bases, both on-premises and cloud-based
• Familiarity with machine-learning concepts
• Ability to prioritize work
• Excellent organizing and communication skills
• Ability to handle multiple tasks and prioritize workload
• Excellent working relationship with engineering, operational, geoscience, IT, and Data teams.
• Ability to objectively manage competing interests and objectives
• Demonstrated visionary and technical innovator.
• Expert in standard applications for drilling (Microsoft Office, morning reporting, etc.)

Occidental is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, marital status, political preference, sexual orientation, gender identity, national origin, protected veteran status, or disability status.