TGS
Overview
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. At TGS, our Data Science team is leading the way in applying AI, machine learning, and cloud-scale computing to some of the toughest challenges in energy and geoscience. We work with one of the most extensive and well-organized energy data libraries in the world - AI-ready by design - giving our scientists and engineers a distinct edge in developing transformative solutions. From foundation models to multimodal AI systems, we are developing next-generation technologies that speed up interpretation, improve workflows, and provide actionable insights. Joining TGS means working directly with cutting-edge ML frameworks, large-scale cloud infrastructure, and advanced data pipelines, while collaborating with top experts across geoscience, engineering, and technology. Purpose & Scope
As a Senior Data Scientist, you will lead key workstreams in energy analytics, focusing on developing and deploying
high-impact ML models
that address complex challenges in exploration, production, and asset management. You will play a central role in scaling advanced AI/ML solutions while mentoring the next generation of data scientists at TGS. Key Responsibilities
Develop and refine advanced ML models to optimize energy operations and improve exploration outcomes. Lead technical project teams in designing, testing, and deploying robust data-driven solutions. Mentor mid-level data scientists, sharing best practices in model development and handling energy datasets. Drive
continuous improvement
in model performance, data quality, and workflow efficiency. Collaborate with engineers, geoscientists, and software teams to integrate solutions into operational workflows. Key Competencies
Advanced Modeling:
Expertise in sophisticated algorithms and model optimization for energy applications. Collaboration:
Strong ability to work effectively with multidisciplinary teams across geoscience and engineering. Leadership:
Experience mentoring others and providing technical guidance to enhance team capabilities. Continuous Innovation:
Keeps pace with the latest energy technologies and ML/AI advances, applying them to TGS projects. Qualifications
Master’s or Ph.D. in Data Science, Computer Science, Engineering, or a related quantitative field. 5–7 years of experience applying machine learning to real-world data problems, preferably in the energy domain. Proven track record of delivering ML solutions from concept to production. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.). Familiarity with cloud-based workflows (AWS preferred) and scalable ML pipelines.
#J-18808-Ljbffr
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. At TGS, our Data Science team is leading the way in applying AI, machine learning, and cloud-scale computing to some of the toughest challenges in energy and geoscience. We work with one of the most extensive and well-organized energy data libraries in the world - AI-ready by design - giving our scientists and engineers a distinct edge in developing transformative solutions. From foundation models to multimodal AI systems, we are developing next-generation technologies that speed up interpretation, improve workflows, and provide actionable insights. Joining TGS means working directly with cutting-edge ML frameworks, large-scale cloud infrastructure, and advanced data pipelines, while collaborating with top experts across geoscience, engineering, and technology. Purpose & Scope
As a Senior Data Scientist, you will lead key workstreams in energy analytics, focusing on developing and deploying
high-impact ML models
that address complex challenges in exploration, production, and asset management. You will play a central role in scaling advanced AI/ML solutions while mentoring the next generation of data scientists at TGS. Key Responsibilities
Develop and refine advanced ML models to optimize energy operations and improve exploration outcomes. Lead technical project teams in designing, testing, and deploying robust data-driven solutions. Mentor mid-level data scientists, sharing best practices in model development and handling energy datasets. Drive
continuous improvement
in model performance, data quality, and workflow efficiency. Collaborate with engineers, geoscientists, and software teams to integrate solutions into operational workflows. Key Competencies
Advanced Modeling:
Expertise in sophisticated algorithms and model optimization for energy applications. Collaboration:
Strong ability to work effectively with multidisciplinary teams across geoscience and engineering. Leadership:
Experience mentoring others and providing technical guidance to enhance team capabilities. Continuous Innovation:
Keeps pace with the latest energy technologies and ML/AI advances, applying them to TGS projects. Qualifications
Master’s or Ph.D. in Data Science, Computer Science, Engineering, or a related quantitative field. 5–7 years of experience applying machine learning to real-world data problems, preferably in the energy domain. Proven track record of delivering ML solutions from concept to production. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.). Familiarity with cloud-based workflows (AWS preferred) and scalable ML pipelines.
#J-18808-Ljbffr