TGS
Overview
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Senior Data Scientist
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TGS 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. Key Responsibilities
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 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. Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Data Infrastructure and Analytics
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Join to apply for the
Senior Data Scientist
role at
TGS 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. Key Responsibilities
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 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. Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Data Infrastructure and Analytics
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