Rising disasters are destabilizing the property insurance market, yet carriers often rely on outdated, incomplete data. ResiQuant is changing that by fusing structural engineering with advanced, agentic AI to expose critical vulnerabilities that standard sources miss, enabling insurers to underwrite disaster-exposed properties with confidence.
Requirements
- 5+ years of experience with the major catastrophe models used by insurance companies (RMS and Verisk) for hurricane, earthquake, severe convective storm, and wildfire modeling.
- Technical understanding about why buildings survive or fail during hurricanes and wildfires.
- Understanding of statistical concepts and practical experience applying them (in A|B testing, causal inference, ML, etc.).
- Experience in programming/modeling in Python.
- Knowledge of database systems.
- Background in structural engineering and/or risk analysis.
- Proficiency/Experience in software development.
Responsibilities
- Collaborate with experienced structural engineers in building a system that collects data and reasons about buildings as a structural engineer
- Participate in product ideation and development.
- Architect and develop a large geospatial database to host multimodal building data and context that will grow over time.
- Write, test, document, and review code according to RQ’s development standards that you would help to define.
- Support the founders in technical integrations with customer systems
- Support customers using the ResiQuant platform and handle domain specific questions
Other
- We're seeking an individual who is passionate about the mission of the company
- We prize candidates who share our company's vision and are ready to help foster an inclusive and collaborative culture.
- As a lean seed startup, we need someone with a scrappy, hands-on approach, eager to evolve alongside our team, and support the company in all stages of growth.
- Location: San Francisco Bay Area (In person)
- Excellent written and verbal communication skills, with the ability to convey complex ideas clearly to diverse audiences.
