Winrock International
Winrock is a recognized leader in U$1. .$1
Agriculture and Sustainability • Clean Energy • Climate Change • Forests and Natural Resource Management • Gender and Social Inclusion
501 - 1000
REDD+ Technical Consultant - GHG Accounting
August 15
🏡 Remote – Anywhere in California
Winrock International
Winrock is a recognized leader in U$1. .$1
Agriculture and Sustainability • Clean Energy • Climate Change • Forests and Natural Resource Management • Gender and Social Inclusion
501 - 1000
Description
• The REDD+ Technical Specialist – Consultant serves as a technical officer and contributes to proposals and business development efforts across ECO team projects in the areas of GHG measurement and monitoring, climate change mitigation and adaptation, climate risk analysis, and ecosystem evaluation. • This position will interact with clients, conduct qualitative technical analyses, perform quantitative problem-solving, and collect and analyze quantitative data. • Specific project activities may include: • Conducting GHG measurement and monitoring activities for companies, governments, and NGOs around the world. • Developing forest inventory design, carbon measurement, and monitoring protocols. • Building capacity building toolkits and training programs for ecosystem assessments. • Creating decision-support tools for the measurement and monitoring of GHG emissions and ecosystem services in the land use and forestry sectors.
Requirements
• Bachelor’s degree in international development or environment-related field required. • Minimum 3-4 years of relevant experience using GIS and remote sensing for GHG accounting and land use mapping required. • Extensive knowledge and proficiency with GIS software (ArcGIS and QGIS). • Experience with forest inventories, biomass data collection and field data collection. • Experience with geostatistical and inferential statistical techniques in a natural resource management context. • Experience with Google Earth Engine (JavaScript and/or Python) is strongly preferred. • Demonstrated knowledge of statistics and modeling (including machine learning). • Proficiency in R/Python for data management and analysis or other relevant platforms. • Demonstrated experience supporting complex projects.
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