Remote Sensing Data Scientist

One Concern is a Menlo Park-based benevolent artificial intelligence company with a mission to increase the global community's resilience to natural hazards. Founded at Stanford University, One Concern enables cities, corporations and citizens to embrace a disaster-free future, through AI-enabled technology, policy, and finance. By combining data science and natural phenomena science we are pursuing a vision for planetary-scale resilience, where everyone lives in a safe, equitable, and sustainable world.
One Concern is seeking  a Data Scientist specializing in Remote Sensing to join our team at One Concern. This role will work on researching, developing and deploying remote sensing based algorithms to support and improve our product offerings at global scale. You should have an in-depth understanding of various remote sensing products for different types of applications, and remote sensing retrieval algorithms (including computer vision, machine learning algorithms etc.).
We work in a highly collaborative, challenging and exciting environment. Our data science and engineering challenges are unique, so you should be comfortable stepping in uncharted territory and excited to create systems that can scale to all disasters and geographies. If you are a problem solver, think out-of-the-box, love challenging yourself, and want to work for a cause, we would love to have you at One Concern.
We are committed to a workplace that reflects the community we serve. We especially encourage women, people of color, and others who are underrepresented in the tech industry to apply.
What will you do
- Conduct research, evaluation, development and implementation of remote sensing related projects, such as change detection and novel target detection- Evaluate and identify appropriate remote sensing datasets as input for various type of projects- Design, build and implement robust and flexible algorithms that can work with noisy, real-world data- Automate remote sensing and/or geospatial workflows- Provide creative and fit-for-purpose technical analyses in collaboration within data science team
Requirements
- Master degree with 3+ years of experience or PhD degree in Computer Science, Urban Planning, Geography, Civil Engineering, or a related field with experience in remote sensing and a good research track record- Strong background in remote sensing and geospatial data, such as Landsat, Sentinel, MODIS, VIIRS, Planet, hyper-spectral, LiDAR, Radar, and/or UAV/drone technique- Demonstrated background developing statistical, machine learning, and/or simulation models using remote sensing datasets- Proficiency in scientific computing with Python, with the ability to quickly pick up new technical skills- Demonstrated ability to apply remote sensing imagery to large scale monitoring and/or modeling in natural ecosystems, agriculture, and/or wildland and urban interface- Strong problem solving skills, with the ability to research, develop, and implement solutions to novel problems- Willingness to expand and learn new skill sets as needed 
Nice to have
- Experience in using deep learning frameworks such as pytorch, keras, or tensorflow- Experience in solving flood detection/water related issue using remote sensing products- Knowledge and/or experience in data assimilation- Excellent presentation and communication skills, with the ability to explain the details of various data sets to people from other fields