As a certified GIS Analyst with over a decade of experience in geospatial data analysis and environmental management, I offer comprehensive solutions for spatial data processing, mapping, and predictive modeling. My expertise spans leveraging tools like QGIS, ArcGIS, and Google Earth Engine to analyze deforestation risks, optimize infrastructure projects, and support sustainable resource management. I specialize in integrating Python (Pandas, NumPy) and R for advanced statistical analysis, machine learning, and automation of geospatial workflows, ensuring data-driven decision-making for environmental and agricultural initiatives.
Key services include:
Spatial Data Mapping & Visualization: Creation of high-precision GIS databases and interactive maps for infrastructure planning, environmental monitoring, and disaster risk assessment.
Predictive Modeling: Development of Python-based models to forecast environmental impacts, such as deforestation trends or water resource availability.
Environmental Impact Assessments (EIA): Compliance with RENCA regulations, socio-environmental conflict resolution, and mitigation strategy design.
Custom GIS Solutions: Tailored systems for agricultural data management, irrigation optimization, and reforestation planning.
My differentiators include a proven track record with international organizations (World Bank, GIZ, GreenLAC), combining GIS expertise with data science certifications (IBM) to deliver actionable insights. I excel in bridging technical complexity with stakeholder communication, ensuring deliverables align with both ecological and business goals. Let’s transform spatial data into strategic assets for your projects.