Arbol is a global climate risk coverage platform and FinTech company offering
full-service solutions for any business looking to analyze and mitigate
exposure to climate risk. Arbol’s products offer parametric coverage which
pays out based on objective data triggers rather than subjective assessment of
loss. Arbol’s key differentiator versus traditional InsurTech or climate
analytics platforms is the complete ecosystem it has built to address climate
risk. This ecosystem includes a massive climate data infrastructure, scalable
product development, automated, instant pricing using an artificial
intelligence underwriter, blockchain-powered operational efficiencies, and
non-traditional risk capacity bringing capital from non-insurance sources. By
combining all these factors, Arbol brings scale, transparency, and efficiency
to parametric coverage.
About the Team
The quant team is responsible for making sense of the terabytes of weather
data Arbol has at its disposal. It forms the connective tissue between more
client-facing teams, such as sales, and back-end roles like data engineering.
You’ll be joining a small team of data scientists, engineers and
meteorologists and will have a unique opportunity to impact many levels of the
firm, such as pricing and product development. This is an ideal position for
someone interested in building machine learning systems for climate data while
taking a deep dive into the parametric insurance industry.
About the Role
In this role, you will research and implement machine learning techniques for
modeling climate data. In addition to analyzing traditional variables such as
temperature and precipitation, you will work with alternative data sources
like radar and satellite imagery to improve existing products and develop new
ones. This will require exciting technical insights coupled with business
understanding gained through interaction with other teams.
We are looking for someone with a quantitative background and an interest in
applying that skillset toward business-driven research problems at the
intersection of climate science and machine learning.
What You'll Be Doing
* Design and implement machine learning approaches for forecasting and generative modeling
* Develop models for climate and weather perils such as heat waves, severe convective storms, and tropical cyclones
* Build robust training and validation pipelines for climate datasets
* Work with risk and insurance teams to perform business-critical analytics
What You'll Need
* BA in statistics, computer science, mathematics, or related quantitative field
* Experience programming in Python
* Experience analyzing large datasets
* Strong problem solving and analytical skills
What's Great to Have
* Graduate degree and/or research experience in a quantitative field
* Comfort with statistics (e.g., linear regression, hypothesis testing)
* Experience working with time series and/or climate data
Candidates for this role must be located in the United States.
Interested, but you don’t meet every qualification? Please apply!
Arbol values the perspectives and experience of candidates with non-
traditional backgrounds and we encourage you to apply even if you do not meet
every requirement.
Accessibility
Arbol is committed to accessibility and inclusivity in the hiring process. As
part of this commitment, we strive to provide reasonable accommodations for
persons with disabilities to enable them to access the hiring process. If you
require an accommodation to apply or interview, please contact
[[email protected]](mailto:[email protected])
Benefits
Arbol is proud to offer its full-time employees competitive compensation and
equity in a high-growth startup. Our health benefits include comprehensive
health, dental, and vision coverage, and an optional flexible spending account
(FSA) to support your health. We offer a 401(k) match to support your future,
and flexible PTO for you to relax and recharge.