Senior 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 lead innovation to produce flood maps from optical imagery. 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 algorithms to extract flood information from optical imagery. You will work with a team of scientists and engineers with expertise in remote sensing (optical and radar), 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.
- Develop new and incorporate existing flood detection methods at the forefront of science and technology
- Improve Cloud to Street’s existing algorithms to extract data from high resolution optical imagery from satellites and other sensors
- Design and manage product development pipelines in response to needs from governments, aid agencies, and insurers
- Collaborate with a team of exceptional scientists and engineers that want you to grow and be successful
- 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
- Scientifically sound approach to remote sensing algorithm development with high resolution satellite imagery
- Code proficiency
- 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
- Commitment to justice, diversity, science, and solidarity with vulnerable communities
- Working with drones or UAV imagery
- Experience with product management
- Understanding of hydrology and physically-based flood models and/or familiarity with data science/machine learning methods and techniques
- Contributing to a shared codebase on GitHub with multiple collaborators
- Using virtual machines on Google Cloud or similar platform
- Working in disaster relief or in low or middle-income countries
As a Cloud to Street member, you:
- Lead development of rigorous science at start-up technology company focused on social impact and represent our organization at scientific and development meetings
- Serve the underserved by reducing the scientific barriers for low and middle income countries to access the information governments, businesses, and communities need to sustainably develop and thrive
- Are in solidarity with vulnerable communities by spending time with flood affected populations and organizations who serve them
- Increase equity by making information accessible to historically marginalized communities and building a diverse and inclusive start-up
Applicants are requested to send their submissions to firstname.lastname@example.org 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.
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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