Geospatial Climate Scientist

About Stand

Stand is a new technology and insurance company revolutionizing how society assesses, mitigates, and adapts to climate risks. Our leadership team has extensive experience in insurance, technology, and climate science: building billions in market value at prior ventures. At Stand, we are rethinking how insurance enables proactive, science-driven resilience.

Existing insurance models often rely on broad exclusions, leaving homeowners without options. At Stand, we leverage advanced deterministic models and cutting-edge analytics to provide personalized risk assessments—helping homeowners secure coverage and take proactive steps toward resilience.

The Role: On the Applied Science team, we build the engines that power Stand’s climate resilience platform. We combine AI, geospatial intelligence, and physics-based simulations into scalable tools that directly shape underwriting, pricing, and customer decision-making.

As a Geospatial Climate Scientist, you will design, deploy, and own large-scale climate and wildfire models from research through production. This is not an academic role — it’s a chance to take state-of-the-art science and engineer it into tools that operate at scale, with measurable impact on society’s ability to adapt to climate change.

Example projects include:

• Developing and productizing wildfire models grounded in the latest science, balancing research depth with business impact.

• Designing interfaces that connect global climate models to local hazard simulations.

• Creating geospatial databases from diverse inputs (weather reanalysis, STAC catalogs, remote sensing) and layering statistical or physics-based models on top.

• Sourcing new large-scale models as we expand into perils beyond wildfire.

This Role Will:

• Lead large-scale wildfire and climate modeling projects from prototyping to production, including expansion into new perils.

• Design pipelines that merge global climate models with local hazard simulations and real-world environmental data.

• Build and maintain scalable infrastructure: appropriate compute resources, data pipelines, frameworks, vendor integrations.

• Manage and augment geospatial and structure-specific datasets to generate actionable insights.

• Collaborate across the company to integrate models, databases, and insights into client-facing workflows.

• Continuously improve model performance, ensuring accuracy and reliability.

Core Skills (Must-Haves):

• Expertise in wildfire and climate modeling: applying established methods (e.g., Rothermel fire spread, level-set methods, ensemble approaches) and using operational/research-grade tools (e.g., FARSITE, WRF-Fire, ELMFIRE).

• Geospatial and data processing fluency: handling large datasets with QGIS, GDAL, STAC catalogs; leveraging LiDAR and remote sensing inputs (e.g., MODIS, Landsat); integrating weather reanalysis data (e.g., ERA5, MERRA-2); and working with SQL databases.

• Multi-scale, multi-modal hazard modeling: combining statistical and physics-based methods across reanalysis, observational, and modeled datasets; producing scalable outputs from global to local simulations.

• Independent programming and workflow ownership: scripting model development in Python (and related libraries); building, testing, and maintaining end-to-end workflows; ensuring reproducibility and reliability without overreliance on AI tooling.

• Modern software practices and deployment: using standardized dev environments (containers, monorepos), CI/CD pipelines, automated testing, and code reviews; deploying at scale to cloud platforms with infrastructure-as-code.

• Collaborative and cross-disciplinary mindset: bridging fire science, geospatial modeling, ML, and business needs; staying current with emerging methods; and pragmatically applying innovations to deliver measurable business impact.

Nice to Have (Helpful, Not Required):

• Advanced degree (Master’s, PhD) in fire science, geospatial modeling, or related fields (e.g., WUI interactions, wind dynamics, hydrology).

• Familiarity with CFD/FEA or other physics-based modeling methods (e.g., combustion, wind flow).

• Working literacy in ML/data science: able to integrate off-the-shelf models and methods, and reason about basic performance metrics (with openness to learning on the job).

• Prior experience in early-stage startups or high-growth environments with rapid iteration and evolving priorities.

Compensation:

The annual base salary range for full-time employees in this position is $160,000 to $200,000 + meaningful Equity Grant.

Compensation decisions are dependent on several factors including, but not limited to, an individual’s qualifications, location where the role is to be performed, internal equity, and alignment with market data.

Additional Benefits:

• Comprehensive benefits including above-market Health, Dental, Vision

• Weekly lunch stipend

• Flexible time off

• 401k plan

Why Join Stand?

At Stand, you’ll be part of a mission-driven team redefining how insurance intersects with climate resilience. This is a unique opportunity to build something transformative—leveraging advanced technology, underwriting expertise, and data-driven insights to create a smarter, more adaptive insurance model.

Equal Opportunity Employment

Stand is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. We believe that diversity enriches the workplace, and we are committed to growing our team with the most talented and passionate people from every community.

Stand Insurance is committed to providing an inclusive and accessible recruitment process. If you require any accommodations during the application or interview process, please let us know by contacting [email protected]. We will work with you to ensure you have the support you need to participate fully.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.