Earth Observation Data Science Specialist
ABOUT PLANETEK ITALIA Planetek Italia is an Italian Vantaggi Company established in 1994, bringing together more than 140 professionals with expertise in Geoinformatics, Space solutions and Earth science. We develop technologies and solutions that transform geospatial data into valuable information, supporting decision-making across environmental monitoring, smart cities, agriculture, defence and security, satellite missions and space exploration. Our expertise spans Earth Observation data processing and analytics, Spatial Data Infrastructures (SDI), satellite software, ground segment systems and cloud-based geospatial services. Among our flagship innovations is Rheticus®, our platform providing continuous geospatial monitoring services to public and private organisations. Planetek Italia is part of the D-Orbit Group, an international Space group combining complementary technologies and expertise across the Space value chain. This creates opportunities to work on ambitious national and international projects, collaborating with multidisciplinary teams and contributing to innovative solutions. We believe in combining technological excellence with curiosity, collaboration and a strong sense of responsibility, developing solutions that help organisations better understand our world and contribute to a more sustainable and secure future. YOUR RESPONSIBILITIES AS “EO DATA SCIENCE SPECIALIST”. You will contribute to Earth Observation and Data Science projects, developing algorithms and AI-based solutions that transform satellite data into valuable information and operational geospatial products. Working alongside engineers, researchers and domain experts, you will have the opportunity to explore emerging technologies,
experiment with innovative approaches and contribute to projects addressing environmental and geospatial challenges. In this role, you will analyze scientific and satellite payload data, contributing to the design and development of processing algorithms that transform raw data into analysis-ready datasets and, ultimately, into value-added products and services. In this role, you will:
· Analyze and process Earth Observation data from satellite sensors, including optical and radar imagery.
· Design, develop and optimize data processing algorithms and workflows to transform raw satellite data into meaningful information.
· Apply machine learning, artificial intelligence and advanced data analytics techniques to Earth Observation applications.
· Develop and test innovative solutions through rapid prototyping, experimentation and performance evaluation.
· Contribute to the development of value-added geospatial products and services for environmental monitoring and other application domains.
- Analyze and process Earth Observation data from optical and radar satellite sensors to address environmental and geospatial challenges.
- Design, implement and optimize algorithms and software pipelines for satellite data processing, applying strong programming skills and a solid understanding of mathematical and physical principles.
- Develop, train and evaluate Deep Learning models for Earth Observation applications, including image classification, object detection,
semantic segmentation and change detection.
- Explore and adapt state-of-the-art AI methods, including Geospatial Foundation Models, assessing their accuracy, generalization capabilities and computational efficiency.
- Develop and validate innovative solutions through rapid prototyping, experimentation and rigorous performance evaluation, translating research outcomes into operational geospatial products and services.
- Collaborate with multidisciplinary teams, research institutions and technology partners to define technical requirements, solve complex problems and integrate solutions into broader processing workflows.
- Support the preparation of technical proposals and tender submissions, including ESA proposals, by contributing to the state-of-the-art review, technical approach, methodology, work plan and validation strategy. YOUR BACKGROUND AND EXPERTISE: You have an MSc or equivalent qualification in Computer Science, Data Science, Mathematics, Physics, Engineering, Earth Sciences or a related field, along with practical experience in Deep Learning, Earth Observation and scientific software development. We are looking for someone with:
- Strong Python programming skills, including the ability to develop, test and maintain reliable scientific software.
- Practical experience in designing, training and evaluating Deep Learning models using frameworks such as PyTorch or TensorFlow.
- Experience working with Earth Observation data and a sound understanding of remote sensing principles, including optical and radar imagery.
- A solid foundation in mathematics and physics, particularly linear algebra, probability, statistics, numerical methods and optimization.
- Experience in image processing and the development of algorithms for a
experiment with innovative approaches and contribute to projects addressing environmental and geospatial challenges. In this role, you will analyze scientific and satellite payload data, contributing to the design and development of processing algorithms that transform raw data into analysis-ready datasets and, ultimately, into value-added products and services. In this role, you will:
· Analyze and process Earth Observation data from satellite sensors, including optical and radar imagery.
· Design, develop and optimize data processing algorithms and workflows to transform raw satellite data into meaningful information.
· Apply machine learning, artificial intelligence and advanced data analytics techniques to Earth Observation applications.
· Develop and test innovative solutions through rapid prototyping, experimentation and performance evaluation.
· Contribute to the development of value-added geospatial products and services for environmental monitoring and other application domains.
- Analyze and process Earth Observation data from optical and radar satellite sensors to address environmental and geospatial challenges.
- Design, implement and optimize algorithms and software pipelines for satellite data processing, applying strong programming skills and a solid understanding of mathematical and physical principles.
- Develop, train and evaluate Deep Learning models for Earth Observation applications, including image classification, object detection,
semantic segmentation and change detection.
- Explore and adapt state-of-the-art AI methods, including Geospatial Foundation Models, assessing their accuracy, generalization capabilities and computational efficiency.
- Develop and validate innovative solutions through rapid prototyping, experimentation and rigorous performance evaluation, translating research outcomes into operational geospatial products and services.
- Collaborate with multidisciplinary teams, research institutions and technology partners to define technical requirements, solve complex problems and integrate solutions into broader processing workflows.
- Support the preparation of technical proposals and tender submissions, including ESA proposals, by contributing to the state-of-the-art review, technical approach, methodology, work plan and validation strategy. YOUR BACKGROUND AND EXPERTISE: You have an MSc or equivalent qualification in Computer Science, Data Science, Mathematics, Physics, Engineering, Earth Sciences or a related field, along with practical experience in Deep Learning, Earth Observation and scientific software development. We are looking for someone with:
- Strong Python programming skills, including the ability to develop, test and maintain reliable scientific software.
- Practical experience in designing, training and evaluating Deep Learning models using frameworks such as PyTorch or TensorFlow.
- Experience working with Earth Observation data and a sound understanding of remote sensing principles, including optical and radar imagery.
- A solid foundation in mathematics and physics, particularly linear algebra, probability, statistics, numerical methods and optimization.
- Experience in image processing and the development of algorithms for a