Data Scientist, Upstream Operations

ExxonMobil is seeking a Data Scientist for Upstream Operations to design, develop, and deploy advanced AI/ML solutions for upstream oil & gas workflows. The role spans production optimization, predictive maintenance, anomaly detection, and GenAI application development, with a strong emphasis on MLOps production readiness.

• Lead design, development, and deployment of advanced AI/ML solutions for upstream oil & gas operations
• Analyze production, well performance, sensor/IoT data, and operational logs to forecast and identify value opportunities
• Build and deploy end-to-end AI/ML solutions with data quality, explainability, and governance
• Develop GenAI applications (chatbots, copilots, multi-agent workflows) and/or time series, optimization, or predictive analytics models
• Ensure production readiness through MLOps (CI/CD, MLflow, monitoring, cost optimization) and mentor peers

You will analyze upstream production, well, sensor/IoT, and operational log data to identify patterns and forecast outcomes, then build end-to-end AI/ML solutions with data quality, explainability, and governance. The stack includes Python, PyTorch, TensorFlow, scikit-learn, and Databricks/Spark, with deployment and sustainment supported by MLOps practices (CI/CD, MLflow, monitoring, cost optimization).

The ideal candidate is a mid-level data scientist with 5+ years delivering production AI/ML solutions, ideally for upstream oil & gas or heavy industrial operations. They are proficient in Python and core ML frameworks (PyTorch, TensorFlow, scikit-learn) with experience using Databricks/Spark, and they can productionize models using MLOps practices including CI/CD and MLflow.