This is a hybrid position which requires 8 days/month in the office. You can be based in our office in Washington DC; WRI Global Office (US). Existing work authorization is required at the time of application submission as WRI is unable to sponsor any visa work sponsorship for this position.
About the Program:
WRIโs Food, Land, and Water (FLW) program focuses on realizing a sustainable future for the worldโs food systems, freshwater, forests, and other natural ecosystems in an integrated fashion. Land & Carbon Lab (LCL) is WRIโs premier hub for geospatial data, analysis, and monitoring of the worldโs land and its natural ecosystems. Our data and monitoring solutions, which include the Global Forest Watch platform, exist to help accelerate implementation and financing of nature-based solutions worldwide. LCL has three main offers: (1) innovation in open geospatial data for land and carbon monitoring, (2) spatial intelligence to support NBS policy and target tracking, and (3) tailored tools that help businesses, governments, civil society organizations, and local communities make data-driven decisions. The Data Lab exists to inspire and fuel data innovation, product development, and technical infrastructure for World Resources Institute (WRI) and our community. We help our partners use advances in data and technology to improve lives, protect nature, and ensure just transitions. The Data Lab is composed of WRIโs core Engineering, Product, and Data teams. The Data Lab supports a wider network of quantitative researchers, data scientists, and product managers embedded across the organization. This position will be based in the Data Labโs Data Team, but will primarily serve FLWโs Supply Chains team, which coordinates efforts across WRIโs various teams and international offices to advance responsible supply chains. This team seeks to enable responsible production, trade, and sourcing of commodities to protect human rights, forests and other ecosystems, and reduce GHG emissions from land-use change.
Job Highlight:
Reporting to the Data Lab Data Science Lead, with a dotted line to a Senior Scientist in Land & Carbon Lab, you will contribute to the research, innovation, implementation and development of new data analysis technologies that leverage artificial intelligence to detect and map crop-field boundaries and identify crop-types and related features with satellite data. You will be supported by a team of data scientists from WRI Data Lab, spatial analysts from WRI Land and Carbon Lab, and supply chain and land use policy experts from our Global and Africa teams.
What will you do:
Spatial Analysis with AI Tools for Agriculture Use Cases (65%):
- Create an open AI model for crop field boundary detection with satellite images that can be used by actors across supply chains and sectors
- Evaluate data products for completion and accuracy, with manual and automated methods
- Evaluate sources of data ranging from imagery to field data to develop effective and efficient modeling strategies
- Assist in crop-type/yield mapping and other mapping endeavors with your AI expertise
Program Development and Administration (10%):-
- Contribute to concept notes, funding proposals, and donor reports
- Support development of workplans and related internal systems and procedures to ensure timely execution of activities and delivery of outputs
- Liaise with external partners and WRI colleagues across programs and countries ยท
- Manage internal communications on project progress from the project team to a wider internal stakeholder group
Writing and Engagement (25%): -
- Contribute to written outputs such as peer-reviewed publications, technical notes, and presentations
- Assist in the development of documentation and standardization of code and data products
- Assist with data-specific outreach and communication from private-sector, government, and non-profit partner organizations, including conducting authoring technical write-ups for one-off analyses
- Assist with the design and coordination of engagement activities, capacity building and other exercises to accelerate uptake of data products
What will you need:
- Education: You have completed a bachelorโs degree in a relevant field (e.g., data science, computer science, information science, engineering, remote sensing, GIS, Geography, geospatial modeling or related fields
- Experience: You have a minimum of 7 years of full-time professional experience in machine learning and remote sensing preferably including 1 year of leadership and/or management experience
- Relevant professional experience includes excellent programming skills in Python or other data science-relevant languages
- Excellent machine learning experience, including model deployment
- Experience using cloud computing platforms including Amazon Web Services and/or Google Cloud Platform to scale and deploy research models
- Experience with of remote sensing, GIS concepts, satellite data and spatial analysis
- Knowledge of current agricultural practices, particularly those use din Latin America
- Strong interpersonal skills and ability to work with teams of individuals and colleagues
- Experience working with distributed and international team members
- Preferred: Familiarity with GIS tools like Esri, GDAL, rasterio, geopandas, Google Earth Engine and cloud-native geospatial data formats (COGs, GeoParquet, STAC, etc.)
- Domain experience with agricultural data (including remote sensing) and models is preferred
- Languages: You have written and oral fluency in English. Knowledge of additional languages including Spanish and Portuguese are a plus
- Requirements: Existing work authorization is required where this position. WRI is unable to authorize visa work authorization
Potential Salary: US salary range is between 96K and 110K USD. Salary is commensurate with experience and other compensable factors.
How to Apply: Please submit a resume with a required cover letter by the date of 23 May 2024. We are unable to consider your application without a cover letter.
You must apply through the WRI Careers portal to be considered.
What we offer:
- Access to the WRI global network with the opportunity to exchange with and learn from passionate colleagues working at the cutting edge of their fields across Asia, Africa, Europe, Latin