Data Scientist, Geospatial

Neara

$110K — $130K *
Energy & Utilities
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of hands-on experience in data science or machine learning, ideally including geospatial data or power grid knowledge.
  • Strong quantitative intuition with excellent communication skills for presenting complex data to stakeholders.
  • Experience in fast-paced, high-growth technology environments is beneficial.
  • Self-driven and able to take ownership of complex projects while adapting to shifting priorities.
  • Collaborative nature, working seamlessly between technical teams and customer stakeholders.
  • Resourceful problem solver with experience handling complex, messy data to achieve clear business outcomes.

Responsibilities

  • Collaborate with customer geospatial and GIS teams on-site to understand and solve spatial challenges.
  • Develop predictive risk models using LiDAR, terrain data, and weather forecasts to mitigate wildfire risks.
  • Translate risk metrics into data-driven insights for utility capital investment decisions.
  • Create and maintain robust data pipelines for processing diverse geospatial datasets.
  • Set quality benchmarks for spatial accuracy and data source alignment.
  • Mentor team members in model training and data analytics best practices.

Benefits

  • Work with advanced spatial data technologies, including LiDAR and satellite imagery, to tackle large-scale engineering issues.
  • Your modeling efforts will actively contribute to reducing wildfire risks and improving energy grid infrastructure.
  • Opportunity to shape the spatial architecture of core products in collaboration with leading ML and software teams.
  • Receive a competitive compensation package with a significant equity component, making you a stakeholder in the company's growth.
Full Job Description
Data Scientist, Geospatial

We're looking for a Data Scientist, Geospatial to join our Houston team, supporting a key regional electric utility. You'll work directly with their team to build physics-backed models on Neara, leveraging complex datasets like LiDAR, GIS, asset records, and weather data. Your work will directly prevent wildfires by simulating vegetation encroachment, predict grid failures under extreme weather loads, and inform capital investment decisions to harden critical infrastructure.

What You Will Do:
  • Embed and collaborate directly with customer geospatial and GIS teams in a hybrid setting, spending time on-site at their offices to deeply understand their data workflows, integrate systems, and solve complex spatial challenges.
  • Build predictive risk models on Neara that combine LiDAR, terrain models, and weather data to simulate conductor sag, sway, and vegetation fall-in risks to directly prevent wildfire ignitions.
  • Translate complex spatial and structural risk metrics into defensible, data-driven insights that inform utility capital investment decisions for grid hardening.
  • Build and maintain robust spatial data pipelines to ingest, clean, vectorize, and integrate diverse geospatial data formats from our utility partner.
  • Establish QA/QC benchmarks for spatial accuracy, coordinate reference system (CRS) transformations, and structural alignment across disparate data sources.
  • Mentor others in best practices for model training, data analytics, and building data-driven products.


Who You Are:
  • 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 and proven experience presenting complex findings to customers and senior leaders.
  • Experience working in fast-paced, high-growth scale-up technology environments is a plus.
  • Self-driven with a bias for action; comfortable taking full ownership of complex projects and adapting quickly 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 a track record of navigating messy, real-world datasets to deliver clear, business-driven outcomes.


What We Offer:
  • Work with an industry-leading, multi-modal spatial data stack - including airborne LiDAR, high-resolution satellite imagery, and physics-enabled digital twins - to solve real-world engineering challenges at immense scale.
  • Your spatial modeling will directly mitigate wildfire risks, optimize utility vegetation management, and harden critical infrastructure across millions of kilometers of energy grids.
  • Shape the spatial architecture of our core product line while collaborating with top-tier ML and software engineers.
  • Enjoy a highly competitive compensation package with a significant equity component, ensuring you are a true stakeholder in our rapid global scaling.


#LI-NT1 #LI-DNP

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