Geospatial Data Scientist

Role Description This full-time remote Geospatial Data Scientist role at Solafune, Inc. focuses on designing, implementing, and optimizing geospatial data pipelines and analytics workflows. The role involves collecting, cleaning, and integrating large geospatial datasets from satellite imagery and other spatial data sources, and performing exploratory analysis to uncover patterns and insights relevant to energy, climate, and environmental applications. The Geospatial Data Scientist will build, validate, and deploy data science models, including spatial and temporal models, to support product features and decision-making. Day-to-day tasks include developing reproducible code and documentation, collaborating with engineering and product teams to translate analytical findings into scalable solutions, and presenting data-driven insights through clear visualizations and reports. The role also involves continuously improving methods, staying current with geospatial tools and methodologies, and contributing to best practices for data quality, integrity, and responsible data use. Qualifications Candidates should possess strong experience in mathematical and information sciences and in working with satellite data and geospatial data. Candidates should possess a solid foundation in Statistics to design experiments, validate models, and interpret uncertainty and significance. Candidates should possess Data Analytics and Data Analysis skills for cleaning, transforming, and interpreting geospatial and tabular datasets. Candidates should possess Data Visualization skills to communicate complex geospatial insights through maps, dashboards, and visual reports. Experience with geospatial tools and libraries (e.g., GIS software, Python geospatial libraries such as GeoPandas, rasterio, or GDAL) is highly beneficial. Proficiency in programming languages commonly used in data science (e.g., Python or R) and experience with version control (e.g., Git) is preferred. Familiarity with cloud-based data platforms and workflows, including working with large-scale or remote sensing datasets, is an advantage. • Ph.D. in mathematical, information science, engineering OR equivalent level of work experience and skills (negotiable) Strong communication skills, ability to work effectively in a remote, cross-functional team, and commitment to inclusive, collaborative problem-solving.