About Stand:

Stand is a new insurance startup revolutionizing how society assesses, mitigates, and adapts to climate risks. Our leadership team has extensive experience in insurance and climate science: building billions in market value at prior ventures in insurtech, wildfire, and real estate. We’re expanding our technical team to develop groundbreaking technologies for quantifying climate risks at the property and community levels, and we’re hiring an exceptional Climate Data Scientist to be a key part of this effort.

How to apply: Interested applicants can email Matt (matt@getstand.com) sharing their resume and a short blurb about their interest in the position.

Background:

Until now, we have known that distinct homes and locations respond differently to climate catastrophes like wildfire. However, we have struggled to assess these mechanisms accurately. Consequently, homeowners are not informed of what they need to do to better protect their homes, and insurance companies give little credit to mitigation work. At Stand, by applying deterministic physics models and cutting-edge artificial intelligence, we add a deep understanding of a home’s unique risk environment to the calculus of writing insurance. This opens up more homes to coverage, encourages proactive measures to protect communities, and nurtures a more sustainable relationship between our neighborhoods and our environment.

The Role:

As a Climate Data Scientist on the Applied Science Team, you will be a key part of developing our models, working closely with other expert engineers, technologists, and our leadership team in a multidisciplinary environment. This role bridges two key efforts: training machine learning models to capture the principles of deterministic physics and repurposing traditional CAT models with simulation data to provide deeper contextualization of location-specific risk. We are seeking a candidate with a strong foundation in climate science and physics fundamentals, paired with functional expertise in statistical analysis and machine learning model development. If you’re excited about pioneering new methods for assessing CAT risk, building innovative machine learning solutions for risk analytics, and enhancing safety and insurance frameworks for homeowners in climate-impacted regions—all while driving value from the ground up—this is the role for you.

What we are looking for:

• Expertise in working within multidisciplinary environments, staying informed on the latest advancements in modeling technologies, and bridging knowledge gaps to foster innovative solutions.

• A solid foundation in machine learning and data science, particularly in areas like catastrophe and probabilistic risk models

• Proficiency in relevant modeling frameworks and tools, such as PyTorch, TensorFlow, or MXNet; bonus if proficient in CAT- specific software like RMS or AIR.

• Proven experience training models on large, heterogeneous datasets to generate accurate risk assessments and actionable insights.

• A passion for solving real-world resiliency challenges, leveraging feedback from both customers and cross-functional teams.