Lead Data Scientist

TGS provides scientific data and intelligence to the global energy sector, enabling energy for all by unlocking vital, data‑driven solutions and knowledge. Through an extensive and diverse energy data library, advanced analytics, cloud‑based applications, and specialized services, we work in a way that is Passionate, Results‑Driven, Collaborative, and Responsible.

The Lead Data Scientist serves as a senior technical contributor within TGS’s Data Science organization, providing strong expertise in scientific machine learning and advanced analytics for complex subsurface problems. This role combines hands‑on model development with technical leadership across major initiatives, supporting the development of reusable learning systems for subsurface data, including foundation‑model‑style representation learning. The position emphasizes scientific rigor, technical influence, and cross‑team collaboration, contributing to the design and evolution of large‑scale learning systems while working alongside other senior technical leaders.

• Lead the design, implementation, and evaluation of scientific machine learning models for subsurface and energy‑related data.
• Contribute to the development of large‑scale representation learning systems, including self‑supervised and weakly supervised approaches.
• Provide technical guidance and review for complex modeling initiatives, ensuring robustness, generalization, and reproducibility.
• Own major technical work streams and deliver scalable analytical solutions from research through deployment.
• Collaborate closely with senior data scientists, domain experts, and engineering teams to align technical solutions with business and scientific objectives.
• Guide experimentation practices, model evaluation standards, and technical documentation.
• Mentor data scientists and support knowledge sharing across the organization.
• Participate in external research activities, publications, or technical collaborations.

• Scientific Machine Learning Expertise:
  Strong understanding of ML applied to physical or scientific systems.
• Large‑Scale Representation Learning:
  Experience with modern deep learning architectures and training workflows for complex datasets.
• Technical Leadership:
  Ability to guide technical work streams and influence outcomes through expertise.
• Experimental Rigor:
  Strong focus on hypothesis‑driven development and reproducible experimentation.
• Collaborative Influence:
  Works effectively within multi‑lead, interdisciplinary environments.
• Mentorship:
  Supports development of technical talent and best practices.

• MSc or PhD in Machine Learning, Data Science, Applied Mathematics, Physics, Geophysics, or a related technical discipline.
• 5–10 years of experience in applied data science or research‑oriented machine learning roles.
• Strong background in modern deep learning and scientific ML applied to complex or large‑scale datasets.
• Experience leading technical initiatives or complex modeling projects.
• Experience in energy, geoscience, or large‑scale scientific/industrial domains preferred.

If you meet the qualifications and are passionate contributing to our team, we encourage you to submit your application by 08/15/2026.