Neara
Neara
Neara razvija programsko opremo za napovedno modeliranje upravljanja komunalnih omrežij, ki ekipam pomaga proaktivno upravljati infrastrukturo ter sprejemati boljše odločitve glede tveganj, vzdrževanja in načrtovanja. Njena platforma simulira dejanske razmere, vključno z močnimi vremenskimi pojavi, da lahko komunalna podjetja ocenijo stanje sredstev, načrtujejo upravljanje vegetacije, prepoznajo ranljivosti in podprejo vključevanje obnovljivih virov energije. Podjetje si prizadeva izboljšati zanesljivost, odpornost in operativno učinkovitost ključnih omrežij.

Geospatial Data Scientist

Develop LiDAR and weather-based risk models for Neara’s digital twin platform for electricity grids. Help utilities prevent wildfires and strengthen infrastructure.

Opis

  • Partner with customer geospatial and GIS teams in a hybrid role.
  • Visit customer offices to learn data workflows, integrate systems, and address spatial challenges.
  • Develop predictive risk models in Neara using LiDAR, terrain models, and weather data.
  • Model conductor sag and sway, along with vegetation fall-in risks, to help prevent wildfire ignitions.
  • Turn spatial and structural risk measures into insights that inform utility capital investment decisions.
  • Build and maintain spatial data pipelines to ingest, clean, vectorize, and combine varied geospatial formats.
  • Set quality assurance benchmarks for spatial accuracy, coordinate reference system transformations, and structural alignment.
  • Mentor colleagues in model training, data analytics, and data-informed product development.

Zahteve

  • At least five years of practical experience in data science or machine learning.
  • Experience with geospatial data or the power grid domain is advantageous.
  • Strong quantitative intuition for data.
  • Excellent communication skills.
  • Demonstrated ability to present complex findings to customers and senior leaders.
  • Experience in fast-paced, high-growth technology scale-ups is advantageous.
  • Self-motivated and action-oriented.
  • Able to take full ownership of complex projects and adapt quickly as priorities change.
  • Collaborative approach with technical teams and external customer stakeholders.
  • A record of turning messy real-world datasets into clear, business-focused outcomes.
  • Able to work in a hybrid setting and visit customer offices.

Ugodnosti

  • Substantial equity component.
  • Work with a leading multimodal spatial data stack.
  • Solve real-world engineering challenges at immense scale.
  • Use spatial modeling to reduce wildfire risk and strengthen critical infrastructure.
  • Help shape the spatial architecture of the core product line.
  • Collaborate with leading machine learning and software engineers.