Quantitative Researcher

Summary

Join Arbol, a global climate risk coverage platform, and contribute to a team responsible for analyzing massive weather datasets. As a data scientist, you will research and implement machine learning techniques for climate data modeling, working with various data sources to improve existing products and develop new ones. You will collaborate with risk and insurance teams on business-critical analytics, designing and implementing machine learning approaches for forecasting and generative modeling. This role requires a quantitative background and experience with Python programming and large datasets. Arbol offers competitive compensation, equity, comprehensive health benefits, 401(k) matching, and flexible PTO.

Requirements

• BA in statistics, computer science, mathematics, or related quantitative field
• Experience programming in Python
• Experience analyzing large datasets
• Strong problem solving and analytical skills

Responsibilities

• 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

Preferred Qualifications

• 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

Benefits

• Competitive compensation and equity in a high-growth startup
• Comprehensive health, dental, and vision coverage
• An optional flexible spending account (FSA) to support your health
• A 401(k) match to support your future
• Flexible PTO for you to relax and recharge