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ClimateAi
Remote Sensing Data Scientist
Over 1 year ago
About the Job
Culture
At ClimateAi we are driven by a united passion to tackle climate change. We believe in a culture of absolute truth and transparency, where feedback is considered an opportunity for us to contribute to each other's personal and professional growth. We recognize the value of diversity and are an equal-opportunity employer.
We hire people who are collaborative, adaptable, communicate well, and love to learn. Expect to give and receive constructive criticism, as we are constantly seeking to push the innovation frontier while simultaneously growing as individuals and as a team.
What you’ll do
Utilizing remote sensing and GIS technologies to analyze and interpret geographical data. This includes processing and analyzing data from various remote sensing sources such as LandSat, MODIS, Sentinel, SMAP, GRACE-FO, OPERA, and others.
Collaborating with a team to develop and implement a comprehensive workflow. This includes coordinating with other team members to ensure the successful completion of the project.
Development of near real-time estimates of flood hazard in an operational context.
Developing and implementing machine learning algorithms for both the mapping of historical flood impacts as well as predictive modeling.
Producing long-term flood hazard projections using proprietary CAi long-term climate projections.
Qualifications:
An Earth Systems science degree (e.g., hydrology, climate, geomorphology, geography). A Master’s degree or PhD is preferred.
Extensive experience with remote sensing and GIS technologies. This includes experience with processing and analyzing data from various remote sensing sources.
Proven experience in developing and implementing machine learning algorithms. This includes experience with various machine learning techniques such as regression, classification, clustering, and deep learning.
Strong problem-solving skills and the ability to work with complex datasets. This includes experience with data cleaning, data transformation, and data visualization.
Excellent communication and teamwork skills. This includes the ability to effectively communicate complex technical concepts to non-technical team members.
Experience with a wide variety of geospatial data, including LULC, soils, DEMs and topographically derived metrics.
Preferred Skills:
Knowledge of Python (familiarity with Julia, R, or JavaScript is an asset)
Experience with collaborative data development (familiarity with AWS, Jupyter, and GitHub is an asset)
Experience manipulating geospatial data in Python (or Julia, R, or JavaScript). Familiarity with QGIS, Whitebox, or GRASS is an asset.
Experience communicating complex findings to a non-technical audience
Compensation
The base annual compensation range for this role for employees based in the US is $130,000-170,000. This salary range is inclusive of several career levels at ClimateAi and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, business need and location.
We are accepting applications on a rolling basis. We are an equal opportunity employer and value diversity at our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
What We Offer You
Competitive salary and equity
Medical, dental, vision benefits
Learning budget per year
Unlimited PTO policy with minimum time off requirements
Flexible working hours on many teams
Culture of diversity and inclusion including employee resource groups
Work with smart, curious, passionate people and be part of the mission to help the world
About the Company
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ClimateAi
About ClimateAi
ClimateAi is on a mission to climate-proof the economy while aiming for zero loss of lives and livelihoods. We use AI to predict the risks of climate change to physical assets, water resources, and biodiversity. Then we generate actionable insights that help stakeholders build strategies for their operations, supply chain planning and regulatory disclosures. We are a fast growing Series-B company that has its roots in the dorms of Stanford University.