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Neara is building physics-enabled digital twins of electricity grids using advanced machine learning to help utilities understand and mitigate risks across millions of kilometers of infrastructure. The company simulates extreme weather and structural stress at network-wide scale to help asset owners pinpoint risks, optimize investments, and build resilient energy systems.
As a Data Scientist, Geospatial, you will embed directly with a key regional electric utility in Houston, working in a hybrid setting with time spent on-site at their offices. You'll build physics-backed predictive risk models that combine LiDAR, terrain models, and weather data to simulate conductor sag, sway, and vegetation fall-in risks—directly preventing wildfire ignitions and grid failures under extreme weather loads.
Key responsibilities include:
- Collaborating directly with customer geospatial and GIS teams to understand data workflows, integrate systems, and solve complex spatial challenges
- Building predictive risk models on Neara's platform that inform utility capital investment decisions for grid hardening
- Translating complex spatial and structural risk metrics into defensible, data-driven insights for senior leaders and customers
- Building and maintaining robust spatial data pipelines to ingest, clean, vectorize, and integrate diverse geospatial data formats
- Establishing QA/QC benchmarks for spatial accuracy, coordinate reference system (CRS) transformations, and structural alignment across data sources
- Mentoring others in best practices for model training, data analytics, and building data-driven products
You'll work with an industry-leading multi-modal spatial data stack including airborne LiDAR, high-resolution satellite imagery, and physics-enabled digital twins. Your work will directly mitigate wildfire risks, optimize utility vegetation management, and harden critical infrastructure.
Requirements:
- 5+ years of hands-on experience in data science or machine learning
- Geospatial data or power grid domain experience is a plus
- Strong quantitative intuition for data with excellent communication skills
- Proven experience presenting complex findings to customers and senior leaders
- Experience in fast-paced, high-growth scale-up technology environments is a plus
- Self-driven with bias for action; comfortable taking full ownership of complex projects and adapting to shifting priorities
- Natural collaborator who thrives at the intersection of technical teams (ML, Software) and external customer stakeholders
- Grounded, resourceful approach to problem-solving with track record of navigating messy, real-world datasets to deliver business-driven outcomes
