$ cat jobs/senior-conservation-data-analyst-engineer-r4458-worldwildlifefundinc1-5317098650b5.json
Senior Conservation Data Analyst/Engineer - R4458
Since our founding in 1961, WWF has been committed to protecting nature and its resources. We understand that nature is our planet’s greatest asset, intrinsically linked to human survival — and that it needs our help. Our work to reverse nature loss and conserve biodiversity has never been more urgent. As the world’s leading conservation organization—with offices on six continents and in nearly 100 countries—our global reach includes the world’s most critical forests, river systems, wetlands, savannas, and ocean habitats. By conserving these places and supporting sustainable livelihoods within them, we can keep the Earth in balance for people, wildlife, and the planet. Major Function Help WWF revolutionize the way we use data and technology to identify conservation opportunities and measure and monitor the impacts of our conservation efforts. The Senior Conservation Data Analyst/Engineer will work with the Global Science team and the WWF network to analyze and maintain environmental and socio-economic data including, but not restricted to, WWF acquired data, government supplied data, commercially acquired data sets, and remotely sensed and in-situ spatial data. The Senior Conservation Data Analyst/Engineer will have broad experience with statistics, data visualization, data management, cloud-based data analysis infrastructures, and current data delivery mechanisms. Understanding of conservation issues on global and local scales is an asset, as is experience working with multiple organizations to harmonize data and data management approaches. The key roles of the data analyst/engineer are to analyze and visualize existing data, work with WWF teams (including Global Science) in developing new analysis approaches, implement methodologies, and develop and maintain data storage and management systems, analysis pipelines, and visualization platforms. This position will be responsible for contributing to the advancement of automated and semi-automated approaches for effici