Data Science Supervisor

Chord Energy-posted 3 months ago
Full-time • Manager
Hybrid • Houston, TX
501-1,000 employees
Oil and Gas Extraction
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The Chord Energy Data Science Supervisor is a working manager that will lead a small team of data scientists/ML engineers while staying hands-on building models yourself. The team develops, deploys, and monitors machine-learning solutions for subsurface (geology, geophysics, reservoir), operations (production, D&C, reliability), and back-office (supply chain, HSE, finance) use cases that drive measurable business value. This role presents an exciting opportunity for a seasoned data science supervisor to contribute to the advancement of Chord's data science transformation, leveraging expertise in data analytics to drive innovation and optimize operational outcomes. This position is located in downtown Houston, TX. Hybrid work schedule is an option for remote work on Mondays and Fridays. Level and salary commensurate with experience.

  • Lead a small team and prioritize and manage the data-science backlog.
  • Translate business objectives into model roadmaps and delivery plans across subsurface, operational, and enterprise domains.
  • Lead the full model lifecycle: problem framing, experiment design, feature engineering, training/validation, deployment, and post-production monitoring with strong MLOps practices.
  • Be hands-on: 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.
  • Bachelor's degree in a quantitative field.
  • 7+ years in data science/ML (including time-series, geospatial, and predictive modeling).
  • 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.
  • 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.
  • Demonstrated ability to work in a team-oriented environment.
  • Excellent presentation skills.
  • Ability to work in a fast-paced and fluid environment; flexible with the demands of a growing company.
  • Ability to meet deadlines.
  • Master's degree or PHD or certification in Data Science or Data Analytics.
  • Familiarity with additional programming languages (SQL, R, C++, etc.).
  • Previous Oil and Gas operator experience.
  • Exposure to Petroleum Engineering and Geoscience workflows.
  • Exposure to the energy sector, particularly unconventional exploitation programs.
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