Climate Risk Quantitative Modeler (Python)

Openkrill; United States; Remote; USD 100,000 - 140,000; Full time

Job summary

Jupiter Intelligence, a global leader in analytics for resilience planning and enterprise climate risk management, is seeking an associate-level contract developer. You will translate climate hazard data into actionable financial metrics like EBITDA impact, CapEx/OpEx, and credit risk while building scalable model infrastructure.

You will gain mentorship, work with Python-based production pipelines, and expand your financial domain knowledge through hands-on projects in a fast-paced environment.

Qualifications

• Degree in a quantitative field or equivalent practical experience.
• Effective Python coding skills with a focus on writing clean, production-quality code.
• Foundational understanding of finance or economics and an eagerness to learn more.
• Basics of data engineering (sourcing, transforming, cleaning data) and standard git workflows.
• Ability to work both independently as well as collaboratively with multiple teams.

Responsibilities

• Build & Scale Pipelines: Write modular, well-tested Python code to move models from research prototypes into production pipelines.
• Support Model Research: Prototyping statistical, econometric, and machine learning models to project climate hazard impacts.
• Data Engineering: Source, clean, and transform diverse financial, building, and hazard datasets.
• Cross-Functional Collaboration: Partner with engineering, product, and client teams to document outputs and communicate analytical findings clearly.

Skills

Python

Data engineering basics

Git workflows

Independent & collaborative

Education

Degree in Computer Science, Finance, Economics, Statistics or related

Tools

Docker

AWS

GCP

Azure

pandas/Polars

Job description

Jupiter Intelligence, a global leader in analytics for resilience planning and enterprise climate risk management, is seeking an associate-level contract developer. You will translate climate hazard data into actionable financial metrics like EBITDA impact, CapEx/OpEx, and credit risk while building scalable model infrastructure.

You will gain mentorship, work with Python-based production pipelines, and expand your financial domain knowledge through hands-on projects in a fast-paced environment.