Principal Research Scientist - Risk (AI)

Location: Remote, New York City

Salary: $180,000–$220,000 per year, plus equity

Company

hirify.global develops AI and machine learning systems with physics-enabled digital twins of electricity grids, helping utilities assess infrastructure risks, optimize investments, and improve resilience.

What you will do

• Contribute to applied research on infrastructure risk, resilience, reliability, and policy.
• Define research agendas and establish standards for risk modeling, uncertainty quantification, model validation, 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 impact of resilience and reliability investments.
• Evaluate the value of additional data, inspections, pole loading analysis, new devices, and remote sensing capabilities.
• Shape the research modeling function, analytical standards, product roadmap, and customer advisory services.

Requirements

• PhD in statistics, applied mathematics, physics, computer science, operations research, engineering, or a comparable record of original research and applied technical work.
• Substantial experience independently defining and executing a research agenda as a senior individual contributor or industry principal.
• Influential publications, patents, or production systems demonstrating research impact.
• Expertise in probabilistic modeling, uncertainty quantification, model validation, scientific computing, and decision-making under incomplete information.
• Experience modeling operational systems, such as insurance or catastrophe models, weather and climate hazards, power-system outages, or reliability engineering.

Culture & Benefits

• Equity component included in the compensation package.
• Access to network-scale utility data and a 3D physics-enabled platform for extreme-event analysis.
• Opportunity to work on novel, under-specified research problems and establish the research agenda.
• Flexible hours and working arrangements.