Data Scientist

Arbol·Remote(New York City, New York)
Data & Analytics

WFA Digital Insight

As the demand for data-driven climate risk solutions surges, Arbol stands out with its cutting-edge FinTech platform. With the global climate risk market expanding rapidly, data scientists with remote work skills are in high demand. Arbol's innovative approach and commitment to transparency make it an exciting place to work, especially for those passionate about applying digital skills to real-world problems. Before applying, candidates should be prepared to showcase their machine learning expertise and experience with diverse datasets.

Job Description

About the Role

Arbol is seeking a Data Scientist to research, develop, and apply machine learning tools to model and price climate and weather risk. The successful candidate will work with a range of weather and geospatial datasets to develop new methodologies and improve existing pricing and modeling tools.

Responsibilities

  • Collaborate within the analytics team and across teams to gain expertise in Arbol's data and pricing infrastructure
  • Develop and improve models for climate and weather perils such as heat waves, severe convective storms, and tropical cyclones
  • Implement, assess, and execute pricing algorithms for a wide array of weather risks
  • Work with sales and executive teams to perform business-critical analytics

Requirements

  • BA in statistics, computer science, mathematics, or related quantitative field
  • Experience in machine learning and data analysis

How to Stand Out

  • Be prepared to showcase your proficiency in machine learning tools and programming languages such as Python or R.
  • Highlight your experience working with diverse datasets, including weather and geospatial data.
  • Emphasize your ability to collaborate with cross-functional teams, including sales and executive teams.
  • Consider including examples of your work in climate risk modeling or a related field in your portfolio.
  • Prepare to discuss how you stay current with industry developments in machine learning and climate risk analysis.

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