Geospatial Data Scientist: Predictive Risk for Utilities

present of AI; Houston (TX); On-site; USD 110,000 - 160,000; Full time

Job summary

present of AI seeks a data scientist to build predictive risk models from messy geospatial data such as LiDAR, terrain and weather. You will turn results into clear, defendable guidance for utility customers and work on-site with the customer team.

You will collaborate across teams, mentor junior staff, and own parts of the data workflow, including spatial pipelines and model validation, to improve decision-making in grid operations.

Qualifications

• Hands-on data science or ML experience over several years.
• Experience with spatial data pipelines and coordinate systems.
• Ability to explain findings to senior stakeholders and customers.
• Willingness to collaborate on-site with customers and mentor others.

Responsibilities

• Build predictive risk models from messy geospatial data (LiDAR, GIS, weather).
• Translate model outputs into actionable advice for a utility customer.
• Work closely with the customer on site and explain findings to non-technical audiences.
• Mentor teammates and promote collaboration and ownership.

Skills

Data science

Machine learning

Spatial data pipelines

Coordinate systems

Stakeholder communication

Collaboration

Tools

LiDAR data

GIS

Python

Model validation

Job description

present of AI seeks a data scientist to build predictive risk models from messy geospatial data such as LiDAR, terrain and weather. You will turn results into clear, defendable guidance for utility customers and work on-site with the customer team.

You will collaborate across teams, mentor junior staff, and own parts of the data workflow, including spatial pipelines and model validation, to improve decision-making in grid operations.