Insurance Structuring Data Scientist
Floodbase
ABOUT FLOODBASE
Floodbase is changing the way businesses and communities adapt to increasing risk of climate change impacts from flooding. Last year, we launched a solution enabling re/insurers and public sector organizations to profitably design, underwrite, and monitor parametric flood insurance products, extending coverage to historically uninsurable locations and risks. Built on nearly a decade of industry-leading and peer-reviewed science, our proprietary solution continuously monitors flooding globally. Floodbase is backed by investors like Lowercarbon Capital, Collaborative Fund, and Floating Point, and trusted by NASA, The UN, Google, FEMA, and more.
As we expand, we are seeking an Insurance Structuring Data Scientist to join our technology team to help us solidify our flood data platform’s position as the preferred solution for the parametric flood insurance market. This role will be responsible for developing principles to guide parametric flood policy structuring leveraging their deep understanding of the scientific and technical principles underlying the Floodbase product. As we grow, this role will push our product forward by establishing novel structuring solutions which minimize basis risk and allow more floods to be covered by parametric flood insurance. The role is hybrid, requiring regular in-office presence in Brooklyn, NY or Boston, MA, and will report to the Chief Product & Strategy Officer.
Here’s what you will do:
Design parametric flood insurance structures that enable (re)insurer partners to efficiently price submissions
- Present and communicate policy payout structures to insurance carriers
- Develop creative structures that balance the needs to (re)insurers and risk holders.
- Actively support insurance carriers through their underwriting process, resolving any questions about Floodbase methodology, payout structure design, and data.
Design pricing models for new flood insurance programs powered by Floodbase
- Develop a repeatable methodology for the program pricing model that can be easily repeated for submissions
- Establish buy-in and acceptance of pricing model with (re)insurance carriers providing capacity behind the program
- Support the commercial team during client outreach, specifically by supporting clients to evaluate their coverage needs and options
Drive development and adoption of novel techniques to estimate flood risk based on Floodbase data
- Use Floodbase data and models to estimate flood risk for businesses, governments, and communities.
- Statistical analysis of flood frequency and risk profiles, and how they change over time.
- Design and improve methodologies and models for estimating flood risk and event damage with Floodbase data.
Who You Are
- Have prior experience with statistical inference in complex dynamical non-stationary systems (especially utilizing extreme value distributions), exploratory data analysis, and data visualization, preferably with data and models associated with climate perils or other hazards using programming languages such as Python or R.
- A doer; you’re ready to roll up your sleeves and are comfortable building methodologies and features within nascent markets with ambiguous requirements.
- Comfortable working with and communicating to a wide variety of stakeholders from machine learning scientists to software engineers, senior management and external audiences.
- Bachelor’s degree in Engineering, Statistics, Mathematics, Earth Science, Data Science, or related quantitative disciplines (a graduate degree is a plus).
- Prior experience in the risk transfer domain preferably within NatCat perils such as wildfire, earthquakes, tropical cyclones, severe convective storms and/or floods is a plus.
- Demonstrated understanding of (re)insurance risk is a plus.
- Experience working with modern technical data platforms including APIs and other automated data delivery mechanisms is a plus.
Salary range
Floodbase offers competitive salaries with regular reviews and adjustments based on performance and industry standards.