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Data Scientist (Geospatial) at CloudWalk. Location Information: Brazil. At CloudWalk, we're building the best payment network on Earth (then other planets 🚀). We're an AI-first fintech unicorn bringing justice to Brazil's broken payment system. We work in the finance sector, a very traditional niche, but we try to do things differently. Where others see coordinates, we see the spatial DNA of financial behavior.. We're looking for a data scientist who thinks in geographic dimensions to uncover patterns that protect merchants, detect fraud, and unlock insights hiding in the intersection of place and payments.. The Geospatial Team. We work with geospatial data from internal and external sources to create ML features and drive business insights. We research and experiment with new algorithms that are more computationally efficient or can leverage spatial data better. We do extensive data visualization with maps to uncover spatial insights and patterns. We value exploration before exploitation—curiosity comes first in spatial analysis. We believe location is more than coordinates—it's behavioral context that drives better decisions. What the Job Entails. Spatial Intelligence:. Apply data science techniques to spatial datasets and location-based problems to uncover financial behavior patterns. Geospatial Model Development:. Design and run experiments on different forms of aggregating spatial data and phenomena, then train and validate geospatial models for business applications. Feature Engineering & Data Enrichment:. Create valuable features for ML models by extracting spatial intelligence from geospatial data sources, perform ETL processes, and deliver enriched data to our internal feature market. Data Pipeline Management:. Build and maintain geospatial data pipelines and analytical workflows using modern data science tools. Spatial Data Discovery & Integration:. Continuously explore and evaluate diverse spatial data sources, research new datasets, and develop creative approaches to "spatialize" existing databases by adding geographic dimensions. Spatial Analysis:. Analyze spatial data patterns and develop spatial models and algorithms to solve business problems. Map-Based Data Visualization:. Create compelling data visualizations with maps to discover insights and communicate spatial findings to stakeholders. What you'll need. Initiative to learn, investigate, experiment with spatial data and geographic problems. Strong statistical and machine learning background, with experience applying these methods to spatial data. Strong experience with map-based data visualization. using tools like Plotly, . Kepler.gl. , or similar mapping libraries. Experience working with spatial data formats (shapefiles, GeoJSON, etc.), coordinate systems, and geospatial dataframes using . geopandas (Python) OR spatial R packages. (sf, sp, etc.). Python proficiency (CloudWalk standard) or strong R skills with willingness to adapt to Python workflows. Strong SQL experience for spatial data queries and analysis. Ability to communicate and debate in English and Portuguese. Nice to Have. Background in Geographic Information Systems (GIS) tools and concepts. Experience with spatial statistics/econometrics and geospatial machine learning methods (e.g. clustering methods like DBSCAN, K-means, hierarchical clustering, or regression methods like GWR, MGWR, SAR). Experience with external data sources (IBGE research, OpenStreetMap, government open datasets). Experience with Google Cloud Platform. Experience with MLOps and deploying geospatial models to production environments. Recruiting process outline:. Online assessment:. An online test to evaluate your theoretical skills and logical reasoning. Technical interview and case presentation. Cultural interview. If you are not willing to take an online quiz and work on a test case, do not apply.. Diversity and inclusion:. We believe in social inclusion, respect, and appreciation of all people. We promote a welcoming work environment, where each CloudWalker can be authentic, regardless of gender, ethnicity, race, religion, sexuality, mobility, disability, or education.