Senior GIS Data Analyst

Job Title: Senior GIS Data Analyst

The Senior GIS Data Analyst will play a key role in developing and integrating machine learning models with geographic information systems (GIS) for the analysis, visualization, and processing of spatial data. This role requires collaboration with cross-functional teams to deliver data-driven solutions, automate geospatial tasks, and provide insights from spatial datasets.

Key Responsibilities:

• Design, develop, and deploy GIS-based machine learning models.
• Collect, clean, and preprocess geospatial data for analysis.
• Develop custom algorithms to analyze large spatial datasets using machine learning techniques.
• Collaborate with senior engineers and data scientists to improve and optimize model performance.
• Integrate machine learning outputs into GIS platforms for mapping, visualization, and analysis.
• Develop and maintain geospatial databases and support data integration efforts.
• Contribute to the creation of tools or scripts to automate geospatial tasks using Python, R, or other relevant languages.
• Prepare technical documentation and reports summarizing project findings and recommendations.

Requirements:

• Bachelor's degree in Geography, Computer Science, Data Science, or a related field.
• 1-2 years of experience with GIS software (e.g., QGIS, ArcGIS).
• Basic experience in machine learning, preferably using Python and popular libraries such as Scikit-learn, TensorFlow, or PyTorch.
• Experience working with geospatial data formats (e.g., shapefiles, GeoJSON, raster, vector).
• Proficient in programming languages such as Python and JavaScript (experience with geospatial libraries like GDAL, Fiona, or Rasterio is a plus).
• Understanding of machine learning concepts such as supervised learning, unsupervised learning, and model evaluation.
• Familiarity with geospatial database management systems (PostGIS, SQL).
• Experience with cloud platforms like AWS, GCP, or Azure, especially for geospatial applications, is an advantage.
• Good understanding of spatial analysis, spatial statistics, and data visualization techniques.
• Strong analytical and problem-solving skills.
• Excellent communication skills and the ability to work in a team-oriented environment.