ABOUT US:

Rising disasters—from earthquakes to wildfires—are destabilizing the property insurance
market, yet carriers often rely on outdated, incomplete data. ResiQuant is changing that.
Founded by Stanford PhDs and backed by a $4M seed round led by LDV Capital, we fuse
structural engineering with advanced, agentic AI to expose critical vulnerabilities that
standard sources miss. Our multi-hazard platform delivers building-level insights so
insurers across the U.S. can underwrite disaster-exposed properties with confidence,
maintain coverage in high-risk regions, and reward resilience where it matters most—
paving the way for a safer, more sustainable future.

ABOUT YOU:

We’re seeking an individual who is passionate about the mission of the company to join us
as Catastrophe Engineer with focus on disaster exposure. 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. The ideal
candidate is excited to apply their knowledge in catastrophe modeling, data science, and
software development, to shape the trajectory of a groundbreaking company.

QUALIFICATIONS:

• 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. OR PhD in relevant field.

• 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.

Please refer the Job description for details