Principal Research Scientist - Risk

Imagine having the power to stress-test an entire power grid against a hurricane or thunderstorm before the clouds even gather. That is the reality we are creating at Neara. We use advanced machine learning to create engineering-grade, physics enabled digital twins of electricity grids across four continents, this helps asset owners understand their biggest challenges and bring the most viable solutions to life across millions of kilometres of infrastructure. By simulating extreme weather and structural stress at a network-wide scale, we empower the world’s largest utilities to pinpoint risks, optimise investments and build a more resilient global energy future. Our team is a collection of brilliant minds who are fanatical about making a tangible difference in the real world, utilising AI and machine learning to accelerate everything from data classification to complex scenario analysis. We have built a special culture where innovation thrives because everyone owns the mission and we need smart, creative people to help us scale this impact to every corner of the globe. Principal Research Scientist - Risk We are seeking an experienced research scientist to lead Neara’s internal research group in topics of system resilience, reliability, and policy. In this role, you will define a research agenda, develop rigorous statistical and decision models, and translate findings into tools and recommendations for utilities managing billions of dollars in capital expenditure. Neara provides network-scale structural, loading, and contextual data across complete overhead electrical systems. As the Principal Research Scientist - Risk, you will use this information to build generalizable models of asset failure and determine the value of additional data, inspections, and interventions. What You Will Do: Build and lead Neara’s applied research function for infrastructure risk and resilience. Direct a team of researchers and establish rigorous standards for risk modeling, uncertainty quantification, and decision-making. Develop predictive models for equipment damage, vegetation failure, outage likelihood and duration, and wildfire-related risk. Design decision models that quantify the operational and economic consequences of resilience and reliability investments, including asset replacement, vegetation management, and network redesign. Quantify the value of data including pole loading analysis, visual inspections, and the installation of new devices and remote sensing capabilities, both empirically and by analytical methods. Who You Are: A PhD in statistics, applied mathematics, physics, computer science, operations research, engineering, or a comparable record of original research and applied technical work. Evidence of having independently defined and led a substantial research program as a group leader or industry principal, demonstrated through influential publications, patents, or production systems.