TÜV SÜD Group – A global leader in the field of testing, inspection, management system certification and product certification renowned for quality, integrity and technical excellence.
Established more than 150 years ago in Germany, TÜV SÜD Group is a leading global provider of technical services with more than 30,000 highly skilled employees across 1,000 offices worldwide. TÜV SÜD Group offers a wide range of testing & product certification, inspection, auditing & system certification, training and knowledge services. We are a premium quality, safety, and sustainability solutions provider.
The Senior Data Scientist, Nature-based Solutions and Digital MRV (NbS & dMRV) leads the development of AI, machine learning, and data science capabilities for TÜV SÜD’s digital climate assurance solutions. He/ She is required to work with environmental, geospatial, and carbon market data, the role transforms complex datasets into scalable digital products and actionable insights. The position oversees the full model lifecycle, from discovery and development to deployment, monitoring, and optimization.
Key Responsibilities
- Environmental Data Science & Analytics
- Develop data-driven solutions and analytical methodologies to support monitoring, reporting, and verification (MRV) activities for Nature-based Solutions projects.
- Analyze environmental, geospatial, remote-sensing, climate, biodiversity, and land-use data to generate actionable insights and support informed decision-making.
- Build predictive models and maintain robust, auditable analytical workflows for carbon accounting, project monitoring, risk assessment, and performance evaluation.
- Artificial Intelligence & Machine Learning
- Design, develop, validate, and deploy AI and machine learning solutions to enhance digital MRV workflows, climate-data products, and decision-making capabilities.
- Apply advanced AI techniques, including predictive analytics, anomaly detection, computer vision, NLP, Generative AI, LLMs, and intelligent automation to improve scalability and operational efficiency.
- Establish and maintain responsible AI practices by ensuring model governance, transparency, explainability, security, data protection, and ongoing performance monitoring.
- Geospatial, Remote-Sensing, and Nature Data Intelligence
- Develop and apply geospatial, Earth Observation, remote-sensing, and GIS analytics to support digital MRV and environmental monitoring activities.
- Monitor and assess key environmental indicators, including vegetation, biomass, carbon stocks, land-use change, ecosystem condition, and project risks using spatial data and analytical models.
- Collaborate with domain experts to translate scientific and carbon-market requirements into scalable, auditable geospatial workflows while evaluating emerging datasets, technologies, and methodologies.
- Digital MRV Product & Platform Development
- Collaborate with product, engineering, and domain teams to translate analytical and AI requirements into scalable dMRV solutions and platform capabilities.
- Develop and integrate production-ready data pipelines, analytical models, AI services, and reusable Python components into digital verification platforms.
- Ensure solutions are secure, traceable, reproducible, and auditable while contributing to system architecture, APIs, and product design decisions.
- Research, Innovation, and Technical Leadership
- Drive innovation by evaluating emerging technologies, leading technical research, feasibility studies, and pilot initiatives across environmental data science, AI, geospatial analytics, and digital climate assurance.
- Provide technical leadership through stakeholder engagement, clear communication of analytical insights, mentoring, and the development of best practices, standards, and long-term data and AI capabilities.
Key Requirement
- Master’s Degree in Computer Science, AI, Machine Learning, Statistics, Applied Mathematics or a related field
- Minimum 6 years of experience in data science, machine learning, artificial intelligence, or advanced analytics
- Strong expertise in Python and modern data science, machine learning, and AI technology ecosystems
- Proven experience developing, deploying, monitoring, and governing AI/ML solutions in production environments
- Solid foundation in statistics, predictive modelling, experimentation, data quality management, and uncertainty assessment
- Experience working with large, complex datasets and cloud-based analytics platforms, software development practices, and automated testing
- Practical knowledge of MLOps, model lifecycle management, reproducible workflows, and responsible AI practices
- Strong analytical, communication, and stakeholder management skills, with the ability to translate complex scientific and business requirements into impactful solutions
We test, we audit, we inspect, we advise. We never stop challenging ourselves for the safety of society and its people. We breathe technology, we strive for professional excellence, and we leave a mark. We take the future into our hands. We are TÜV SÜD Group.