Senior Lead Data Scientist

TGS provides scientific data and intelligence to companies active in the energy sector. In addition to a global, extensive and diverse energy data library, TGS offers specialized services such as advanced processing and analytics alongside cloud-based data applications and solutions. TGS Prediktor is a leading asset management and real-time data management solutions provider to renewable and energy asset owners.

Serves as a senior technical leader within TGS’s Data Science organization, contributing deep expertise in scientific machine learning and advanced analytics. This role provides high-level technical guidance across complex, large-scale initiatives, supporting the development of reusable learning systems for subsurface data, including foundation‑model–style representation learning.

The position emphasizes scientific rigor, technical mentorship, and cross‑team collaboration, helping translate advanced research into scalable, high‑impact solutions across the energy value chain.

• Provide senior technical oversight and review for advanced analytics and scientific machine learning initiatives, with emphasis on robustness, generalization, and reproducibility.
• Contribute to the design, training, and evaluation of large-scale learning systems, including self-supervised and weakly supervised approaches.
• Collaborate with data science leadership and cross-functional teams to align technical work with strategic and commercial objectives.
• Guide experimentation practices, evaluation standards, and scientific communication across complex projects.
• Mentor data scientists, fostering a culture of scientific rigor and technical excellence.
• Support high-impact client engagements and external collaborations by providing technical depth alongside other senior leaders.
• Engage with external research communities and industry partners to help keep TGS aligned with emerging AI-for-science best practices.

• Scientific Machine Learning Leadership:
  Ability to guide advanced ML efforts applied to physical and scientific systems.
• Large-Scale Representation Learning:
  Experience with modern deep learning architectures and training paradigms associated with foundation models.
• Experimental Rigor:
  Strong focus on hypothesis-driven development and reproducible experimentation.
• Collaborative Influence:
  Shapes technical outcomes through collaboration rather than formal authority.
• Mentorship:
  Proven ability to elevate experienced technical talent.

• MSc or PhD in Machine Learning, Data Science, Applied Mathematics, Physics, Geophysics, or a related technical discipline.
• Typically 7+ 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 working collaboratively across research, engineering, and business-facing teams.
• Energy, geoscience, or large-scale scientific/industrial domain experience preferred.

If you are passionate about cloud technology and developer platforms, and ready to help evolve our multi-cloud strategy, please submit your application by February 27, 2026.