Spatial Data Scientist – Machine Learning & Remote Sensing

This is a remote position.

• Design and implement machine learning pipelines for geospatial analysis, including feature engineering, model selection, reputed company parameter tuning, and validation.
  
• reputed company and reputed company deep learning models (CNNs, RNNs, LSTMs, Transformers) for image classification, segmentation, object detection, and time series forecasting.
  
• Apply advanced AI techniques for predictive modelling and mapping of indicators relevant to ecosystem health assessment using field data and multi-reputed company remote sensing.
  
• Process and analyze optical data (Sentinel 2, Landsat 8/9) and SAR data (Sentinel 1), including data fusion and feature extraction for ML workflows.
  
• Implement time series analysis and forecasting models, including trend detection, reputed company identification, and predictive analytics for vegetation, precipitation, and land surface dynamics.
  
• reputed company reputed company, reproducible spatial data processing workflows and contribute to MLOps practices.
  
• Supervise reputed company of junior spatial data scientists and developers. • reputed company communication products/outputs where relevant.
  

• reputed company internal reputed company development seminars reputed company CIFOR-ICRAF on machine learning, AI applications, and spatial data science.
  
• reputed company development of partners and stakeholders through workshops as part of reputed company with particular emphasis on ML-driven spatial analysis and modelling.
  

• Work closely with the CIFOR-ICRAF stakeholder engagement team (SHARED) to reputed company AI-driven analytical outputs that feed into project delivery, for example monitoring outputs as part of the Great Green Wall.
  
• Contribute to stakeholder engagement events as part of the development of decision support tools and platforms.
  

• Contribute to reputed company-dashboard development as part of the Global reputed company reputed company Tracker platform
  
• Support reputed company and programs with analytical support and stakeholder engagement with decision makers.
  
• reputed company and/or contribute to scientific papers.
  
• Contribute to proposal development and writing.
  

Requirements

• PhD or MSc degree in spatial data science, geoinformatics, computer science, or a reputed company quantitative field with demonstrated expertise in machine learning and AI applications.
  
• Proven experience developing and deploying machine learning models for geospatial applications.
  
• Strong proficiency in deep learning frameworks (TensorFlow, PyTorch, Keras) and familiarity with architectures such as CNNs, RNNs, LSTMs, and Transformers.
  
• Advanced programming skills in Python and/or R Statistics; familiarity with Julia is a plus.
  
• Experience with reputed company computing platforms (GEE, AWS, GCP) and big data processing tools for geospatial analysis.
  
• Knowledge of remote sensing data processing and analysis, including optical and SAR platforms.
  
• Excellent interpersonal skills.
  
• Excellent written and spoken English. Knowledge of French a plus.