Senior Data Scientist (Actuary)

| New York, NY, USA
Employer Provided Salary: 150,000-180,000 Annually
Salary data is provided by the employer. Please note this is not a guarantee of compensation.
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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 Quantitative Research team is responsible for making sense of the terabytes of weather data Arbol has at its disposal and using those insights to drive the business. You’ll be joining a team of data scientists, software 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 applying their statistical skills to weather insurance while taking a deep dive into the parametric insurance industry.

About the Role

Arbol is seeking a Senior Data Scientist to join our Quantitative Research team. In this role, you'll serve as a generalist data scientist, working on a variety of projects including developing pricing algorithms, creating risk management tools, and identifying potential new products through data analysis. This position requires strong technical skills alongside a keen business acumen developed through collaboration with other teams. We seek candidates with experience in data science and statistical analysis who are eager to take ownership of key projects. Because you will be periodically interacting with traditional insurers, some actuarial experience is required (though this is not the focus of the role).

What You'll Be Doing

  • Design and implement pricing and risk management algorithms (Python)
  • Work with Arbol’s insurance and derivatives teams to perform business-critical analytics
  • Present and digest sophisticated analyses for both internal and external stakeholders

What You'll Need

  • BA in computer science, statistics, or related quantitative field
  • Experience programming in Python
  • Comfort with statistics (e.g., regression, hypothesis testing)
  • Strong problem solving and analytical skills
  • ACAS certification and 2+ years of actuarial experience at an insurer

What's Great to Have

  • Software development experience, including coding best practices
  • Experience working with time series and/or climate data

Candidates for this role must be located in the United States.

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.


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]


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 20 days of PTO for you to relax and recharge. 

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419 Park Avenue South, New York, NY 10016

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