GIS Data Analyst

We invite applications from suitably qualified candidates. Position Overview: - We are seeking a motivated and detail-oriented GIS Data Analyst with expertise in Geographic Information Systems (GIS) and Python programming. The successful candidate will be responsible for collecting, analyzing, and interpreting spatial and non-spatial data to support decision-making processes. Key Responsibilities: - Collect, clean, and analyze spatial and non-spatial datasets from multiple sources. - Utilize GIS software (e.g. ArcGIS, QGIS) to perform spatial analysis and create maps and visualizations. - Develop and maintain Python scripts to automate data processing and analysis tasks. - Interpret and present data insights through reports, dashboards, and presentations. - Collaborate with cross-functional teams to support data-driven decision-making. - Ensure data accuracy, integrity, and consistency across various datasets. - Conduct geospatial modeling and statistical analysis to address complex problems. - Identify trends, patterns, and anomalies within datasets and provide actionable insights. - Document processes and methodologies for reproducibility and knowledge sharing. Required Skills and Qualifications - Bachelor's degree in Geography, Geology, Data Science, Computer Science, or a related field. - 2-3 years of experience in data analysis with a focus on GIS and Python programming. - Proficiency in GIS tools (e.g., ArcGIS, QGIS) and geospatial data processing. - Strong Python programming skills for data manipulation, automation, and analysis (e.g., Pandas, NumPy, GeoPandas). - Experience working with spatial databases (e.g., PostGIS, SQLite) and SQL queries. Have practical knowledge of database management. - Strong analytical and problem-solving skills with attention to detail. - Excellent communication skills, both written and verbal. Preferred Skills: - Knowledge of remote sensing techniques and satellite imagery analysis. - Familiarity with cloud platforms (e.g Google Cloud) for data storage and processing. - Experience with web mapping technologies (e.g., Leaflet, Mapbox) - Understand statistical and machine-learning techniques for geospatial data.