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Research Scientist (Machine Learning / Remote Sensing Data Assimilation)

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Cloud to Street is the leading flood mapping platform designed to protect the world’s most climate-vulnerable communities. By harnessing global satellites, advanced science, and community intelligence, we monitor worldwide floods in near real-time and remotely analyze local flood exposure at a click of a button. Our mission is to ensure that all vulnerable governments finally access the high quality information they need to prepare for and respond to increasing catastrophes. Founded by two women at Yale and seeded by Google, Cloud to Street is or has been used by governments across 15 countries. We are on track to enable new flood protection and insurance for 10 million people in the next 5 years.

We are looking for a best-in-class data fusion scientist to lead innovation to downscale passive microwave sensors using radar and optical high resolution flood maps. You should apply if you are eager to use science to reduce the impact of catastrophic flooding and build an innovative and sustainable organization. In this role, you will lead the development of machine learning based algorithms trained on high resolution flood events to downscale passive microwave sensors. You will work with a team of scientists and engineers with expertise in remote sensing (optical, radar, and passive microwave), hydrology, climate, social vulnerability, UX, and machine learning to i) optimize and improve Cloud to Street’s current flood mapping system and ii) build the next generation of tools to ensure financial protection from floods in marginalized communities

Primary Responsibilities

Characteristics of a Successful Candidate

Useful Experience

As a Cloud to Street member, you:

To Apply

Applicants are requested to send their submissions to hiring@cloudtostreet.info with: 

Applications will be accepted until the position is filled. Priority candidates will be reviewed by March 2nd with the intent to start the right candidate as soon as possible.

Cloud to Street is devoted to building an inclusive and diverse company. Women, people of color, and individuals with disabilities are especially encouraged to apply. 

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