Quantitative Python Engineer for Climate Risk (FinTech)

Arbol; United States; Remote; USD 140,000 - 180,000; Full time

Job summary

Arbol seeks a Quantitative Python Engineer to help build tools that power climate risk analytics and financial services. You’ll design features, build Python libraries, and create APIs and microservices that drive pricing and risk management.

You’ll collaborate with quants, traders, and product teams to deliver impactful solutions, write clean, well-tested code, and help shape the engineering roadmap. This role is based in New York City with a competitive salary.

Qualifications

• Ideal candidates will have at least three years of professional Python experience.
• Strong understanding of the software development lifecycle.
• Genuine enthusiasm for learning and innovation.

Responsibilities

• Design and implement new features for Arbol's risk management tools and trading platforms
• Build and maintain Python libraries and frameworks used across the organization
• Develop APIs and microservices that integrate with external data providers and internal systems
• Create tools and applications for traders, risk managers, and senior management
• Build, test, deploy and maintain algorithms for pricing and risk management
• Work with Arbol’s insurance and derivatives teams to perform business-critical analytics

Skills

Python

NumPy

Pandas

Tools

APIs

Microservices

Testing frameworks

Job description

Arbol seeks a Quantitative Python Engineer to help build tools that power climate risk analytics and financial services. You’ll design features, build Python libraries, and create APIs and microservices that drive pricing and risk management.

You’ll collaborate with quants, traders, and product teams to deliver impactful solutions, write clean, well-tested code, and help shape the engineering roadmap. This role is based in New York City with a competitive salary.