Operational Data Assimilation Scientist - Next-Gen Weather

AEOLUS; San Francisco, Northern (CA, KY); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Aeolus is building a next-generation data assimilation (DA) framework in Julia that interfaces with our open-source Earth system modeling ecosystem, NumericalEarth. We are looking for a Research Scientist to join the Data Assimilation team to operationalize that framework and generate skillful, calibrated forecasts by assimilating multispectral observations from public and proprietary sources.

The role focuses on transforming research prototypes into robust, cycling workflows, scaling cases with

Qualifications

• PhD in meteorology, atmospheric physics, applied mathematics, or a related engineering discipline.
• Experience with operational data assimilation and/or setting up quasi-realistic DA cases with WRFDA, JEDI, or a similar framework.
• Experience bridging remote-sensing observations and models, from observation operators to quality control.
• Fluency in Fortran and Python.
• Working knowledge of DA algorithms and their practical failure modes.

Responsibilities

• Operationalize the DA framework by turning research prototypes into reliable workflows.
• Scale existing cases with new datasets, including multispectral satellite radiances and other observations.
• Develop new workflows as model components come online, focusing on convective-scale phenomena.
• Integrate ML-based DA algorithms and define interfaces/benchmarks against baselines.
• Build demonstration and stress-test cases that expose gaps in data quality-control infrastructure.

Skills

Fortran

Python

Data assimilation

Education

PhD in meteorology / atmospheric physics / applied mathematics / engineering

Tools

WRFDA

JEDI

Job description

Aeolus is building a next-generation data assimilation (DA) framework in Julia that interfaces with our open-source Earth system modeling ecosystem, NumericalEarth. We are looking for a Research Scientist to join the Data Assimilation team to operationalize that framework and generate skillful, calibrated forecasts by assimilating multispectral observations from public and proprietary sources.

The role focuses on transforming research prototypes into robust, cycling workflows, scaling cases with