Clr
Senior Engineer, Data Science
Oklahoma City, OK · Senior
Sponsorship not specifiedDetected 20 days ago
PythonSQLDatabricksMachine LearningTensorFlowPyTorchscikit-learnData EngineeringData ScienceLLMsA/B TestingSupply ChainLeadershipCommunicationAdaptability
About the role
- The ideal candidate combines a Master of Science in Data Science with strong applied analytics capability, solid data engineering skills, and practical oil and gas domain experience comparable to a seasoned upstream engineering background.
- Executes complex AI initiatives from ideation and discovery through model development, deployment, and sustainment as part of integrated, enterprise-level teams.
- Applies Machine Learning Ops best practices to automate training, testing, deployment, monitoring, and model lifecycle management at scale in production environments.
Responsibilities
- Builds strong partnerships and cross-functional relationships with geoscience, engineering, operations, commercial, IT, and leadership stakeholders to drive adoption and sustain business impact.
Requirements
- Proficiency in Python and SQL
Nice to have
- Oil and gas industry experience, particularly in upstream engineering, subsurface, drilling and completions, production operations, or commercial energy analytics.
- Background in computational sciences, optimization, or high-performance computing for engineering applications.
- Familiarity with enterprise data governance, security, and responsible AI practices in regulated environments.
- Five (5) or more years of combined oil and gas engineering/domain experience and applied data science experience.
- Physical Requirements and Working Conditions
- Requires prolonged sitting, some bending and stooping.
- Occasional lifting up to 25 pounds.
- Manual dexterity sufficient to operate a computer keyboard and calculator.
Skills
- Collaborates
- Action oriented
- Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
- Drives results
- Consistently achieving results, even under tough circumstances.
- Self-development
- Actively seeking new ways to grow and be challenged using both formal and informal development channels.
- Nimble learning
- Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder.
- Situational adaptability
- Adapting approach and demeanor in real time to match the shifting demands of different situations.
- Instills trust
This listing is sourced directly from Clr's careers page and normalized into a canonical job model.