Data Scientist, Geospatial (AI)

Location: Houston, United States; hybrid work with regular on-site collaboration at customer offices

Salary: $140K–$160K base salary, plus equity

Company

hirify.global uses AI, machine learning, physics-enabled digital twins, and advanced spatial data to help electricity utilities assess infrastructure risks and improve grid resilience.

What you will do

• Collaborate with customer geospatial and GIS teams to understand data workflows, integrate systems, and solve spatial challenges.
• Build predictive risk models using LiDAR, terrain, weather, and utility asset data to simulate conductor sag, sway, and vegetation fall-in risks.
• Translate spatial and structural risk metrics into data-driven insights for utility capital investment and grid hardening.
• Build and maintain pipelines for ingesting, cleaning, vectorizing, and integrating diverse geospatial data formats.
• Establish QA/QC benchmarks for spatial accuracy, CRS transformations, and structural alignment across data sources.
• Mentor others in model training, data analytics, and data-driven product development.

Requirements

• 5+ years of hands-on experience in data science or machine learning.
• Strong quantitative intuition and the ability to communicate complex findings to customers and senior leaders.
• Experience navigating messy, real-world datasets and delivering clear, business-driven outcomes.
• Ability to collaborate across ML, software, geospatial, GIS, and external customer teams.
• Ability to work in a hybrid setting in Houston and spend time on-site at customer offices.

Nice to have

• Experience with geospatial data or power grid systems.
• Experience in a fast-paced, high-growth scale-up technology environment.

Culture & Benefits

• Work with airborne LiDAR, high-resolution satellite imagery, and physics-enabled digital twins.
• Contribute to wildfire risk mitigation, utility vegetation management, and critical infrastructure resilience.
• Shape the spatial architecture of a core product while collaborating with ML and software engineers.
• Receive a competitive compensation package with a significant equity component.