Principal Research Scientist – Risk

This is a fully remote position, open to applicants in New York.

📋 Description

• Contribute to Neara's applied research initiatives focused on infrastructure risk and resilience.

• Set high standards for risk modeling, uncertainty quantification, and decision-making processes.

• Create predictive models that assess equipment damage, vegetation failures, outage probabilities and durations, as well as wildfire-related risks.

• Develop decision models that evaluate the operational and economic impacts of investments in resilience and reliability.

• Measure the value of data derived from pole loading analyses, visual inspections, new technologies, and remote sensing capabilities.

• Outline a research agenda and convert findings into actionable tools and recommendations for utility companies.

• Construct generalizable models of asset failure utilizing network-scale structural, loading, and contextual data.

⛳️ Requirements

• PhD in statistics, applied mathematics, physics, computer science, operations research, engineering, or a similar background with a proven record of original research and applied technical work.

• Demonstrated ability to independently define, lead, and execute a significant research agenda as a senior individual contributor or industry expert.

• Noteworthy publications, patents, or production systems that showcase research impact.

• Acknowledged subject matter expert with substantial technical authority.

• Experience in establishing research direction without the need for direct managerial oversight.

• Extensive expertise in probabilistic modeling, uncertainty quantification, model validation, scientific computing, and decision-making with incomplete information.

• Significant experience in modeling operational systems.

• Relevant background in insurance or catastrophe modeling, weather forecasting and climate hazards, power system outages, or reliability engineering.

🏝️ Benefits

• Equity component.

• Access to exclusive network-scale utility data.

• Opportunity to influence the research modeling function and agenda.

• Key role in shaping the long-term product roadmap, analytical standards, and customer advisory services.

• Flexible hours and working arrangements.