Remote Sensing Scientist
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 remote sensing scientist to join our growing team in Brooklyn, New York. You should apply if you are eager to employ your top notch geospatial talents and coding skills toward reducing the impact of catastrophic flooding in low and middle-income countries, and especially if you are committed to building an innovative and sustainable organization designed to reduce scientific barriers to flood information. In the role, you will take ownership of the pipeline for delivering flood maps and analytics to end users, and have the opportunity to make scientific advances a reality for those who need it the most. You will interact directly with decision makers, both remotely and in the field, who use the data we produce. Broadly, you will have an immediate impact on what we do at Cloud to Street, from designing new flood detection algorithms to automating high-quality impact reports for governments.
- Incorporate new flood detection methods at the forefront of science/technology for improving flood data extraction from satellite imagery
- Develop creative data science and visualization tools to optimize the use of flood data by end users, e.g., through incorporating new methods/data sets for measuring flood impact
- Manage a remote sensing analyst to produce daily flood reports for ongoing projects and to assess algorithm performance for new project scoping
- Identify opportunities for automation of regular tasks, data analysis, and report production
- Represent Cloud to Street at scientific conferences and present technical demos for low and middle-income country end users
- You tell us! Each member has skills not in their job description that are important for our growth. We would love to hear your unique talents and how we can help each other grow.
Characteristics of a Successful Candidate
- Master’s or PhD in geography, earth science, atmospheric science, engineering, computer science, or a related field with a focus on remote sensing and/or geospatial analysis
- Self-starter with ability to work within a fast-paced and rapid-evolving startup
- Eagerness to learn new skills and help with the task at hand
- Prioritizes justice, diversity, science, and solidarity with vulnerable communities
- Experience with remote sensing algorithm building and accuracy assessments
- Understanding of hydrology and physically-based flood models and/or familiarity with data science/machine learning methods and techniques
- Experience contributing to a shared codebase on GitHub with multiple collaborators
- Experience using virtual machines on Google Cloud or similar platform
- Experience working in disaster relief or in low or middle-income countries
Applicants are requested to send their submissions to email@example.com with:
- Subject line: Remote Sensing Scientist, Cloud to Street
- Attached CV/resume
- Relevant publications
- Paragraph expressing interest
Applications will be accepted until the position is filled. Priority candidates will be reviewed by July 15 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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