Logo
Pear VC

Disaster Exposure Data Engineer

Pear VC, San Francisco, California, United States, 94199


About us:

Across the globe, rapid urbanization and escalating climate change impacts are driving skyrocketing risks from disasters like earthquakes, hurricanes, and wildfires-yet exposed building inventories are unstandardized, static, and incomplete, preventing decision making across verticals, from public policy to real estate transactions.

At ResiQuant, we're on a mission to empower insurers, financial institutions, and asset managers with the world's first single source of truth for property data that actually provides engineering-relevant building characteristics.

Founded by Stanford PhDs and backed by Pear VC, ResiQuant is driven by an unwavering commitment to protect communities and businesses from the devastating impacts of disasters. We believe that every organization deserves access to best-in-class property risk intelligence to build resilience against the storms to come-and we won't stop until this is the norm, not the exception.

About You:

We're seeking an individual who is passionate about the mission of the company to join us as Data Scientist 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.

Start date:

Immediate

Qualifications :Experience with the major catastrophe models used by insurance companies (RMS and Verisk) for hurricane, earthquake, severe convective storm, and wildfire modeling.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.What will make you stand out:

Proficiency/Experience in software development.Proficiency/Experience working with multimodal data sources (e.g., voice, imagery, text) for AI model training.Proficiency/Experience collecting and interpreting data from interviews.What drives us:

Impact: we are driven by a shared mission to address a paramount challenge of our timeResolve: we believe that hard work and resilience yield extraordinary outcomesUrgency: we are motivated to outpace rapid urbanization and escalating disaster impactsWhy join RQ :

Opportunity to be involved in an early-stage startup and build the culture you want to see.Chance to pioneer and disrupt one of the world's largest industries.Experience firsthand the tangible impact of what you build.Day to day:

Further develop the domain-specific knowledge base for AI model training alongside the founders.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.Interface with product managers, software development, and AI team to understand product goals and data needs.Write, test, document, and review code according to RQ's development standards that you would help to define.What we offer:

Competitive salary commensurate with experienceEquity in the company as a founding memberVibrant tech startup environmentCompetitive company 401(k) program with company matchingHealth insuranceWorking on the challenge of our generation with other passionate people