Executive Summary

The Geospatial Data Scientist will utilize geospatial technology and data science techniques to develop predictive models from large datasets. This hybrid position involves collaboration with diverse teams, focusing on machine learning applications related to urban growth, transportation analysis, and resource management, with an emphasis on migrating data from AWS to Databricks.

Required Skills and Experience

• Machine Learning: 3+ years of experience developing predictive models with large datasets.
• Geospatial Analysis: Proficiency in analyzing spatial data for urban and resource applications.
• Data Visualization Tools: Experience with Tableau or ArcGIS for presenting insights.
• AWS Cloud Migration: Hands-on experience transitioning data to cloud platforms.
• Python/R Programming: Solid programming skills for data manipulation and model development.
• Database Management: Experience with SQL databases for querying geospatial data.
• Data Wrangling: Skills in handling and cleaning complex datasets for analysis.

Desired Skills and Experience

• Databricks: Knowledge of Databricks for processing big data.
• GIS Software: Familiarity with GIS software for spatial data mapping.
• Statistical Analysis: Experience with statistical methods for data interpretation.
• Project Management Tools: Proficiency with tools like Jira for task management.
• Domain Knowledge: Understanding of urban planning and transportation systems.

Preferred Qualifications

• Team Collaboration: Strong team player with effective communication skills.
• Problem-Solving: Creative approach to tackling complex data challenges.
• Adaptability: Ability to thrive in a dynamic and evolving work environment.

Required Education

Bachelor's degree in Data Science, Geospatial Science, Computer Science, or a related field; a Master’s degree is preferred.