Chord Energy is looking to solve business problems in subsurface, operations, and back-office use cases by developing, deploying, and monitoring machine-learning solutions that drive measurable business value.
Requirements
- Proficiency in Python (pandas, scikit-learn) and SQL;
- Experience with Azure ML/MLflow and deploying models to production.
- Domain familiarity with upstream oil & gas workflows (subsurface and operations) and the ability to translate expert knowledge into features and experiments.
- Familiarity with additional programming languages (SQL, R, C++, etc.).
- Exposure to Petroleum Engineering and Geoscience workflows.
- Exposure to the energy sector, particularly unconventional exploitation programs.
- Experience with machine learning frameworks and tools such as scikit-learn, TensorFlow, or PyTorch.
Responsibilities
- Lead the full model lifecycle—problem framing, experiment design, feature engineering, training/validation, deployment, and post-production monitoring—with strong MLOps practices.
- Write Python/SQL, build and review notebooks/pipelines, perform code reviews, and mentor the team on statistical rigor and software engineering.
- Maintain and evolve the team toolset (Azure ML, OpenAI/Azure AI Foundry, Snowflake/feature store, MLflow), ensuring reliability, security, cost control, and access governance.
- Prioritize and manage the data-science backlog; translate business objectives into model roadmaps and delivery plans across subsurface, operational, and enterprise domains.
- Build models yourself and lead a small team of data scientists/ML engineers.
- Develop, deploy, and monitor machine-learning solutions for subsurface, operations, and back-office use cases.
- Perform statistical analysis and data modeling using Python and SQL.
Other
- Bachelor’s degree in a quantitative field.
- 7+ years in data science/ML (including time-series, geospatial, and predictive modeling).
- Strong coaching, prioritization, and stakeholder-management skills; able to convert business problems into robust, scalable model solutions and communicate outcomes clearly.
- Strong interpersonal and collaborative skills.
- Ability to work in a fast-paced and fluid environment; flexible with the demands of a growing company.
