Radar Remote Sensing Scientist


Cloud to Street is the recognized authority on using satellites and AI to track floods anywhere on earth. Founded by two climate experts with initial funding from Google, the team comes from NASA, Facebook, Google, Willis Towers Watson, and Oscar Insurance. Our platform has been used by 17 countries to fill critical information gaps for disaster planning and response, and is the official emergency flood mapping provider to the United Nations. The technology is now enabling insurers to expand protection to billions of uninsured assets and people through partnerships with Munich RE and Willis Towers Watson. We recently raised a large seed from top investors that will be announced soon.


We are looking for a best-in-class remote sensing scientist with expertise in analysis of high-resolution synthetic aperture radar (SAR) imagery to lead algorithm development for flood detection. You will work closely with our team’s remote sensing scientists, machine learning engineers, and hydrologists to build novel flood analytics and practical decision-support tools for disaster responders, flood managers, and insurers. You should be able to creatively integrate high resolution SAR observations with auxiliary datasets to tackle challenging problems, such as making flood maps in urban areas.

Who You Are


This role is based in our Brooklyn, NY office. Candidates based in New York City, Austin, TX, Santa Fe, NM, Boston MA, or Tucson, AZ areas are preferred. Remote work is possible within UTC -8 to UTC +1 time zones (Pacific Standard Time to Central European Time).

To Apply

Send resume with "Radar Remote Sensing Scientist" in the subject line. Submissions should include an attached CV/resume and a paragraph of interest. Relevant past projects and/or publications are optional for submission.

Cloud to Street is devoted to building an inclusive and diverse company. Black, Indigenous, and people of color; women, queer people, and all gender identities, and individuals with disabilities are especially encouraged to apply.


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