Job Description

About the Role

We’re partnering with a large, operations-focused organization to hire a Data Scientist (GIS) to support analytics initiatives within their operations function. This role applies geospatial data and advanced analytics to help improve operational efficiency, service reliability, and planning decisions.

The work is highly analytical and engineering-focused, with models built directly in Snowflake and used as inputs into downstream optimization and planning systems.

What You’ll Work On

Geospatial Modeling & Time Estimation

• Develop data-driven models to estimate operational timing across different service and facility interactions
• Leverage GPS data and geofencing techniques to understand behavior across locations
• Incorporate contextual variables such as:
• Geography and location characteristics
• Customer and service attributes
• Site complexity and external conditions (e.g., weather, time-based patterns)
• Produce reliable, explainable time estimates that support planning and decision-making

Facility & Location Analytics

• Model turnaround and processing time across different types of locations
• Analyze performance variability based on operational and environmental factors
• Apply polygon- and radius-based geofencing to capture location-specific behavior
• Quantify how conditions impact operational flow and timing outcomes

Technical Environment

• Primary development and modeling in Snowflake
• Build and engineer transformations and analytical processes directly in Snowflake
• Modeling approaches may include:
• Percentile-based time estimates
• Aggregations such as averages and medians by service and location attributes
• Data sources include:
• Latitude/longitude data
• High-frequency GPS signals
• Location and facility reference data

What We’re Looking For

• Strong hands-on experience with Snowflake
• Advanced SQL skills
• Python for analytics and data engineering
• Solid understanding of core GIS concepts, including:
• Spatial joins
• Polygons
• Geofencing
• Experience with traditional GIS tools (e.g., ArcGIS) is a plus, but this is not a cartography or visualization-focused role
• Background in geospatial data engineering and modeling is key

Interview Process

• Two One hour video interviews

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