Data Scientist, Geospatial (AI)

Location: Houston, United States; hybrid collaboration with customer geospatial and GIS teams, including time spent on-site at their offices.

Base salary: $140K–$160K plus equity.

Company

hirify.global uses machine learning and physics-enabled digital twins to model electricity grids, simulate extreme weather and structural stress, and help utilities improve infrastructure resilience.

What you will do

• Collaborate directly with customer geospatial and GIS teams to understand data workflows, integrate systems, and solve spatial challenges.
• Build predictive risk models combining LiDAR, terrain models, and weather 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 decisions.
• Build and maintain spatial data 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 for data and excellent communication skills.
• Proven experience presenting complex findings to customers and senior leaders.
• Experience taking ownership of complex projects, adapting to shifting priorities, and delivering business-driven outcomes from messy real-world datasets.
• Ability to collaborate across ML, software, and external customer stakeholder groups.

Nice to have

• Geospatial data or power grid domain experience.
• Experience working in fast-paced, high-growth scale-up technology environments.

Culture & Benefits

• Work with airborne LiDAR, high-resolution satellite imagery, and physics-enabled digital twins.
• Address real-world engineering challenges across millions of kilometres of energy-grid infrastructure.
• Contribute to wildfire-risk mitigation, utility vegetation management, and critical-infrastructure hardening.
• 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.