Data Scientist, Wells Engineering

At IPT Global your models won't die in a pilot. With a team of around 100 people, you'll work directly with the people making operational decisions and see the impact of your work quickly.

Check out for more information on our world-class team.

Job Description

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

Qualifications

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

Additional Information

All your information will be kept confidential according to EEO guidelines.