We are seeking a skilled and inquisitive Geospatial Data Scientist to support the development of advanced geospatial analytics and machine learning capabilities at Neural. This role plays a key part in designing and delivering data products that address critical challenges in environmental monitoring, infrastructure risk, and spatial decision-making. You will collaborate with engineers, scientists, and product managers to build models that process satellite, aerial, and vector data, enabling clients to extract meaningful insights from complex spatial datasets.

Your day-to-day will involve building workflows to clean, analyze, and transform large-scale spatial and temporal datasets. You’ll apply modern statistical and machine learning techniques to detect patterns, model trends, and support predictive analytics. Whether estimating climate impacts or classifying remote sensing images, your work will inform real-world decisions across industries.

This position is ideal for individuals who love to work at the intersection of spatial intelligence and AI, are passionate about open data and tools, and thrive in collaborative, mission-driven environments.

• Develop machine learning models using geospatial data (e.g., satellite imagery, LiDAR, vector features).
• Implement data pipelines to handle large spatial datasets from multiple sensors and platforms.
• Perform exploratory data analysis (EDA) and visualization using modern geospatial tools.
• Apply supervised and unsupervised learning techniques for classification, segmentation, and prediction.
• Collaborate with engineers and product stakeholders to operationalize analytics in cloud environments.
• Document workflows, write technical summaries, and contribute to publications and reports.

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