Job Title:
Data Scientist Intern (12 months) - Starting Summer 2026
Project Title: Evaluating steering performance of downhole drilling tools
About SLB:
We are a global technology company, driving energy innovation for a balanced planet.
At SLB we create amazing technology that unlocks access to energy for the benefit of all. That is our purpose. As innovators, that has been our mission for 100 years. We are facing the world’s greatest balancing act- how to simultaneously reduce emissions and meet the world’s growing energy demands. We’re working on that answer. Every day, a step closer.
Our collective future depends on decarbonizing the fossil fuel industry, while innovating a new energy landscape. It’s what drives us. Ensuring progress for people and the planet, on the journey to net zero and beyond. For a balanced planet.
Our purpose: Together, we create amazing technology that unlocks access to energy for the benefit of all. You can find out more about us on
Location:
Cambridge, UK
SLB Cambridge Research (SCR) is part of SLB’s global network of research and engineering centres. SCR is a dynamic, multidisciplinary environment with state-of-the-art research and computing facilities. We work on applied research projects in the physical sciences to meet the current and future challenges of the industry.
Description & Scope:
The goal of this project is to develop metrics to evaluate the steering performance of downhole drilling tools. Drilling data acquired from the field need to be systematically processed and analysed for this purpose. Performance indicators for steering will be formulated and calculated using this data. Available jobs in the database will be then scored according to the derived metrices to identify problematics runs.
Deliverables:
1. Develop a workflow to access field data from operations
2. Develop algorithms to process and visualize field data
3. Formulate steering performance metrics
4. Identify problematic runs using the scores
Qualifications:
5. Studying a Masters in Data Science, Mechanical Engineering or a related discipline
6. Python / matlab
7. Accessing/processing/analysing time series data
8. Basic understanding on structural mechanics