Data Scientist, Wells Engineering

We're looking for an engineer who knows how wells are designed, drilled, and completed, and wants to spend their time building the models that make that work safer, faster, and cheaper. You'll turn well barrier assurance and verification data into predictions and recommendations that engineering and operations teams use to make real decisions, and you'll own that work end to end, from understanding the problem on the rig to putting a working model in front of the people who need it.
This role is a strong fit for a drilling, completions, wells, or well integrity engineer who has already been writing Python and building models alongside their day job and wants to make that the job. We'll support you in deepening your machine learning skills; what we can't teach is the operational intuition you bring.
What you'll work on
Building models to support pressure test interpretation, including positive and inflow tests
Evaluating time series data from well control equipment, such as BOPs and associated control systems, and developing predictive maintenance models
Developing monitoring models for sustained or abnormal annulus pressure behavior across the well lifecycle
Tracking barrier element status and verification history to surface gaps and prioritize integrity work
Cleaning and structuring data into something models can trust
Explaining model results clearly to wells engineers, integrity teams, and leadership, including when the model shouldn't be trusted
What you bring
A degree in petroleum, mechanical, or a related engineering discipline
Demonstrable hands-on wells engineering or well integrity experience at an operator, drilling contractor, or oilfield services company
Working proficiency in with range of data science tools
At least one model or analytical tool you built that was actually used to inform engineering or operational decisions
A solid grasp of statistics and the judgment to know when an engineering assessment beats a data-driven one
Nice to have
Experience with well integrity management systems or barrier assurance workflows
Experience with time series analysis or anomaly detection on pressure and sensor data
Exposure to cloud platforms or deploying models into production
SQL experience

Employment type
Full-time

Work arrangement
Hybrid