Remote Sensing Analyst
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 creative and committed remote sensing analyst to join our team. You should apply if you are interested in using your geospatial talents toward reducing the impact of flooding in low and middle-income countries. In this role, you will take deep ownership over being the first line of defense for monitoring automatic flood and precipitation alerts from our platform, and report visual and statistical risks to users in a digestible and actionable way. You will work closely with our remote sensing scientists and project managers to improve Cloud to Street’s near real-time flood monitoring product. This position is a good fit for you if you enjoy working on real-world disaster risk reduction through applied scientific insights.
- Prepare visual and statistical reports on flooding situations to be used by government users in low and middle-income countries for disaster response
- Monitor active flood events for ongoing Cloud to Street projects through a variety of sources (geospatial data, media events, local reports)
- Work collaboratively with remote sensing scientists to validate and improve Cloud to Street’s flood products and science benchmarks
- Explore potential flood mapping projects by collecting visual and historic data on a case by case basis
- Execute and troubleshoot code for our internal automated flood mapping systems
- Report directly to Deployment Team Managers
Characteristics of a Successful Candidate
- Bachelors in geography, earth science, atmospheric science, engineering, computer science, or a related field with a focus on remote sensing and/or geospatial analysis
- Eagerness to learn new skills and an openness to guidance on interpreting flood maps
- Proficiency and hands-on experience in remote sensing principles and methods
- Demonstrated ability in producing maps, coding visual data, and/or formatting summary reports
- Ability to work both independently and collaboratively with a scrappy startup mentality
- Commitment to justice, diversity, science, and solidarity with vulnerable communities
- Experience with QGIS or comparable GIS software
- Familiarity with data science methods and techniques
- Past projects assessing accuracy of or quality controlling geospatial data sets
- Comfortability with meteorological and/or climate data
- Understanding of hydrology and physical-based flood models
- Our ideal candidate brings most of these experiences, but we expect most of our candidates may have particular strengths or experiences with one area more than another
As a Cloud to Street member, you:
- Lead development of scalable technology at start-up technology company focused on social impact and sustainable development
- 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 Analyst, Cloud to Street
- Attached CV/resume
- Paragraph describing relevant projects or research with samples if possible
- Paragraph expressing interest
Applications will be accepted until December 1st.
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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