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Neara is building physics-enabled digital twins of electricity grids using advanced machine learning to help utilities understand infrastructure risks and optimize resilience investments. The company operates across four continents, simulating extreme weather and structural stress at network-wide scale to enable utilities to pinpoint risks and build more resilient energy systems.
As Principal Research Scientist - Risk, you will lead Neara's internal research agenda in system resilience, reliability, and policy. You will define research direction, develop rigorous statistical and decision models, and translate findings into tools and recommendations for utilities managing billions in capital expenditure. Working with network-scale structural, loading, and contextual data across complete overhead electrical systems, you will build generalizable models of asset failure and determine the value of additional data, inspections, and interventions.
Key responsibilities include:
- Contributing to Neara's applied research function for infrastructure risk and resilience
- Establishing rigorous standards for risk modeling, uncertainty quantification, and decision-making
- Developing predictive models for equipment damage, vegetation failure, outage likelihood and duration, and wildfire-related risk
- Designing decision models that quantify operational and economic consequences of resilience and reliability investments, including asset replacement, vegetation management, and network redesign
- Quantifying the value of data including pole loading analysis, visual inspections, and new devices and remote sensing capabilities through empirical and analytical methods
- Helping develop and build Neara's research modeling function, establishing agenda and identifying preferred methods
- Playing a central role in shaping long-term product roadmap, analytical standards, and customer advisory services
The role offers flexible hours and working arrangements, access to unique network-scale utility data unavailable in other research settings, and the opportunity to work on cutting-edge infrastructure challenges.
Requirements:
- PhD in statistics, applied mathematics, physics, computer science, operations research, engineering, or comparable record of original research and applied technical work
- Proven track record of independently defining, driving, and executing substantial research agenda as senior individual contributor or industry principal, demonstrated through influential publications, patents, or production systems
- Recognized subject matter expert with deep technical authority and history of setting research direction without direct management oversight
- Extensive experience in probabilistic modeling, uncertainty quantification, model validation, scientific computing, and decision-making under incomplete information
- Substantial experience modeling operational systems, particularly in insurance/catastrophe modeling, weather prediction and climate hazard, power system outages, or reliability engineering
