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Machine Learning Data Science Consultant

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Cloud to Street is the leading remote flood mapping system designed for the world’s most vulnerable communities. Our platform harnesses global satellites, advanced science and community intelligence to monitor floods in near real time around the world and remotely analyze local flood exposure at a click of a button. Our mission is to ensure that all vulnerable governments can finally access the high quality information they need to prepare and respond to increasing catastrophes. Cloud to Street is or has been used by governments in 11 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 machine learning and computer vision specialist to develop and deploy models to fill data gaps in flood maps across satellite sensors. You should apply if you are eager to employ your machine learning skills to reduce the impact of catastrophic flooding in low and middle income countries. The algorithms you develop will enable governments to rescue vulnerable populations and provide relief in the days following extreme flood events. You will collaborate with a team of remote sensing scientists and hydrologists who will provide rapid feedback, support your workflow, and teach you about their fields.  This is an opportunity to make real-world impact in the humanitarian aid sector, with room for creativity to find the best solution regardless of approach (e.g., classification and regression trees, convolutional neural networks, etc.).

Primary Responsibilities

Characteristics of a Successful Candidate

Useful Experience

To Apply

Applicants are requested to send their submissions to with: 

Applications will be accepted until the position is filled. Priority candidates will be reviewed by August 5 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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