We are looking for a **Mid-level Geospatial Data Scientist** to join our Data Science team. The professional will be responsible for analyzing, processing, and modeling **georeferenced data** from various sources (satellite imagery, drones, sensors, and topographic data), applying data science and artificial intelligence techniques to generate insights and support decision-making in strategic projects. **Responsibilities** * Process, clean, and integrate **geospatial data** in different formats (raster, vector, shapefiles, GeoTIFF, among others); * Perform spatial and geostatistical analyses, including interpolations, segmentations, and feature extraction; * Automate processing workflows and analyses using **Python**; * Use GIS tools such as **QGIS**, **ArcGIS**, or similar for visualization, manipulation, and spatial analysis; * Apply **machine learning** models to geographic data (classification, regression, clustering, etc.); * Develop scalable pipelines and scripts for handling large volumes of data; * Collaborate with multidisciplinary teams (engineering, environment, energy, planning) to produce technical reports and deliverables; * Support the development of AI solutions applied to geospatial problems. **Differentiators** * Knowledge of **neural networks** (CNNs applied to satellite or drone imagery); * Experience with **cloud computing** (AWS, GCP, Azure) and geospatial big data (Dask, Spark, PostGIS); * Familiarity with **Geospatial Deep Learning** (TensorFlow, PyTorch, Semantic Segmentation, etc.); * Experience with **LiDAR**, **DTM/DSM**, or **temporal analysis** of imagery; * Knowledge of **spatial databases** (PostGIS, SpatiaLite). * Degree in Engineering, Data Science, Geoprocessing, Geography, Computer Science, or related fields; * Proven experience with **georeferenced data** and GIS tools (QGIS, ArcGIS, GDAL, etc.); * Proficiency in **Python** and libraries for geospatial data (**GeoPandas, Rasterio, Shapely, PyProj, Fiona**); * Knowledge of **statistics, exploratory data analysis, and basic machine learning** (scikit-learn, XGBoost, etc.); * Experience handling large datasets and automating analytical routines.