Principal Research Scientist - Risk

present of AI; New York (NY); On-site; USD 150,000 - 210,000; Full time

Job summary

Neara in the US is seeking a senior researcher to define their own research agenda on grid risk and resilience, turning insights into practical tools and guidance for utilities. The candidate should have deep experience in probabilistic modeling, uncertainty quantification, and decision making with incomplete data, plus a proven record of independent research leadership. The role involves shaping AI-driven approaches with a physics-based digital twin for grid applications.

Qualifications

• Strong candidate has deep work in probabilistic modeling, uncertainty quantification and decision making with incomplete data.
• Proven track record leading research independently.
• Experience applying research to real-world utility problems is highly valued.

Responsibilities

• Set and own the research agenda on grid risk and resilience.
• Translate research findings into practical tools and actionable guidance for utilities.
• Lead research efforts independently with impact on utility practices and investments.

Skills

Probabilistic risk modeling

Uncertainty quantification

Research agenda leadership

Power system reliability

Job description

The role asks for a senior researcher who can set their own research agenda on grid risk and resilience, then turn it into practical tools and advice for utilities. A strong candidate brings deep work in probabilistic modeling, uncertainty quantification and decision making with incomplete data, plus a record of leading research independently. Experience with operational systems such as catastrophe modeling, weather hazards, power outages or reliability engineering matters most.

How it fits the AI era

Machine learning already helps classify data and run scenario analysis at network scale, so the role leans on AI to speed up modeling and simulation. What stays human is judgment: framing the right research questions, setting standards for uncertainty and validation, and deciding what the findings mean for real investment choices. The scientist shapes how AI outputs are trusted and used, not just produced.

How it builds AI experience

Working with a physics based digital twin of real grids gives hands on exposure to applying AI and machine learning to asset failure, outage and wildfire risk at large scale. The person would learn to test and validate models against network wide utility data and to weigh the value of new data sources like inspections and remote sensing. Building this means pairing statistical rigor with practical questions about where AI predictions hold up and where they need checking.

Worth showing

• Probabilistic risk modeling
• Uncertainty quantification
• Research agenda leadership
• Power system reliability

About Neara

A physics-based 3D digital twin of the electricity network, so utilities can simulate a storm or a fire before it happens rather than inspect poles after.

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.