Job Overview This role sits at the intersection of geospatial research, data science, and engineering for candidates who seek continuous learning in a startup environment. Success in this role means delivering reliable geospatial analytics that move from research to production/prototyping, and are actively used by future customers. Responsibilities ・Develop innovative technologies for R&D projects leveraging geospatial and satellite data using Python ・Translate research concepts into prototype-ready systems using modern frameworks ・Design, develop, and validate geospatial models and analytical algorithms (e.g. change detection, classification, forecasting), and validate spatial analytics techniques ・Design and implement early data processing pipelines (ingestion → analytics → storage) when required ・Conduct extensive research on scientific methodologies, ground-truth information, datasets, and emerging algorithms relevant to assigned projects ・Take ownership of project deliverables under the guidance of the direct manager ・Prepare and deliver high-quality presentations, technical reports, and actionable recommendations to management and stakeholders ・Collaborate with cross-functional teams to evaluate technical feasibility, improve analytical workflows, and support innovation initiatives when required

Required Skills (Must haves) ・2+ years of experience in agriculture focused analytics ・In lieu of direct agriculture analytics experience: Ph.D. or equivalent level of work experience and demonstrated skills in adjacent domains (e.g. environmental monitoring, forestry, land use, or similar applied geospatial fields), with a degree in Computer Science, Data Science, AI, Physics, Mathematics, or a related field (negotiable) ・Solid programming experience with Python (typically 1-5 years) ・Experience in working with satellite data, geospatial data (e.g. Rasterio, PyStack, GeoPandas, Shapely) ・Research experience, preferably with a focus on geospatial information or remote sensing, mathematical and information sciences ・Experience with geospatial data formats and tools (GeoTIFF, COG, STAC, GDAL) ・Experience with SQL and database management (PostgreSQL, PostGIS) ・Experience in AI, Machine Learning, Computer Vision (e.g. scikit-learn, scikit-image, TensorFlow, PyTorch), or a related field is preferable ・Strong analytical thinking, problem-solving skills, and the ability to work independently

Additional Skills (Nice to haves) ・Exposure to cloud platforms (AWS/GCP/Azure) ・Experience building interactive data applications or dashboards (e.g. Dash/Plotly, Streamlit) is a strong advantage ・Engineering practices, or a habit of writing clean, maintainable code ・Strong interest or experience in remote sensing and ground monitoring ・Experience participating in data science competitions such as Kaggle and its results

Ideal Candidate We are looking for candidates who are experienced in the following: ・Geospatial & remote sensing: GDAL, Rasterio, STAC, COG ・Cloud service platform: AWS, Azure, GCP ・Development languages: Python ・Data & ML: NumPy, GeoPandas, Pandas, and AI frameworks such as scikit-learn, PyTorch and TensorFlow ・Systems: Docker, APIs ・Database: PostgreSQL, PostGIS ・Collaboration: Github, Slack, Notion ・GIS (e.g., ArcGIS, QGIS) ・AI tools: Claude Code, Codex, GitHub Copilot, etc.