Satellite Remote-Sensing Fellow — Paid On‑Site Research

Rainmaker Technology Corporation; El Segundo (CA); On-site; USD 81,244 - 97,315; Full time

Benefits offered by this job

Full health coverage

Lunch provided in-office

EV charging at HQ

Job summary

Rainmaker Technology Corporation is offering a paid, full-time Satellite Remote Sensing Fellowship in El Segundo. You will join the satellite remote-sensing group and take ownership of a concrete computational workstream while contributing to retrieval, validation, automation, and operational-support tasks.

Ideal candidates are early-career researchers or recent graduates with strong Python skills and a background in atmospheric remote sensing, satellite meteorology, or related fields.

Qualifications

• Strong quantitative and programming ability, preferably in Python.
• Experience with atmospheric remote sensing, satellite meteorology, physics, or related fields.
• Interest in microwave sounders and retrieval methods.

Responsibilities

• Acquire, process, collocate, and quality-control microwave, polar-orbiting, and geostationary satellite observations.
• Reproduce an existing retrieval or operational baseline before testing improvements.
• Validate satellite products against radar, NWP, soundings, and Rainmaker measurements.
• Quantify detection skill, bias, uncertainty, and representativeness by meteorological regime.
• Implement retrieval improvements justified by project and data.
• Build reproducible workflows for Rainmaker scientists to run and extend.
• Present findings to satellite scientists, meteorologists, and leadership.
• Deliver a final artifact such as a dataset or retrieval benchmark.

Skills

Python

Quantitative skills

Satellite remote sensing

Education

Undergraduate student

Master's student

PhD student

Recent graduate

Tools

Git

NumPy

Pandas

Job description

Rainmaker Technology Corporation is offering a paid, full-time Satellite Remote Sensing Fellowship in El Segundo. You will join the satellite remote-sensing group and take ownership of a concrete computational workstream while contributing to retrieval, validation, automation, and operational-support tasks.

Ideal candidates are early-career researchers or recent graduates with strong Python skills and a background in atmospheric remote sensing, satellite meteorology, or related fields.