Climate Risk ML Research Intern

Descartes Underwriting Group; United States; Remote; USD 28,000 - 41,000; Full time

Benefits offered by this job

Competitive internship stipend

Meal vouchers (Swile)

60% public transport reimbursement

Job summary

Descartes Underwriting is seeking an enthusiastic R&D Data Scientist Intern for a 6‑month end‑of‑studies internship. You will bridge academic research and real-world industrial application by exploring climate science and machine learning to build models that shape risk assessment and pricing.

Join a cross‑functional team, work on state‑of‑the‑art methods, and contribute to insurance solutions for natural perils and cyber risk in a dynamic, international environment.

Qualifications

• Student in university/engineering with a research‑oriented track in applied mathematics, physics, climate science or machine learning.
• Ideally a previous internship in data science, physics or climate modelling.

Responsibilities

• Translate open-research problems into valuable business assets by exploring literature, implementing and benchmarking state‑of‑the‑art machine learning methods and climate models.
• Leverage large-scale climate data to develop and evaluate new models quantifying natural perils (wildfires, hail, floods, tropical cyclones, etc).
• Collaborate with Underwriting and Software teams to deploy experimental models into production pricing tools.
• Refine algorithms to improve accuracy, speed, and reliability in assessing climate risks.

Skills

Python

Statistics

Applied mathematics

Machine learning

Attention to detail

English fluency

Education

University/Engineering program with research track in applied maths/physics/climate or ML

Tools

Pandas

scikit-learn

Job description

Descartes Underwriting is seeking an enthusiastic R&D Data Scientist Intern for a 6‑month end‑of‑studies internship. You will bridge academic research and real-world industrial application by exploring climate science and machine learning to build models that shape risk assessment and pricing.

Join a cross‑functional team, work on state‑of‑the‑art methods, and contribute to insurance solutions for natural perils and cyber risk in a dynamic, international environment.