Senior Conservation Data Analyst/Engineer - R4458

Company Description

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.

Job Description

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 efficient and responsive geospatial data processing and analyses for key conservation metrics.  

Key Responsibilities  

• Support the development and application of data analysis and visualization methodologies and pipelines with the WWF scientists and program managers.  

• Manage product and projects to deliver key outputs including the Conservation Navigator 

• Perform analyses for select projects; apply advanced statistical and spatial analysis and programming as needed. 

• Manage GIS software licensing and distribute software licenses to all users in the Network.   

• Coordinate with software vendors to obtain and renew licenses and to handle support requests.  

• Maintain data repositories, including GIS servers (e.g., Google Earth Engine, ArcGIS Enterprise, and ArcGIS Online) by keeping software up to date. Maintain knowledge of other data platforms, including cloud-based platforms (e.g., AWS, Google Cloud, Azure) and cloud-based relational databases for use as needed.  

• Develops and maintains data storage management systems, analysis pipelines, and visualization platforms to support conservation data needs. 

• Collaborates with WWF teams to develop and implement new analytical approaches and methodologies. 

• Analyzes and visualizes environmental and socioeconomic data to support decision-making and conservation outcomes. 

• Evaluates and applies new developments in technology, data analysis and open-source tools for analysis and data visualization (e.g. D3.js, QGIS, AI).  

• Other duties as assigned.  

Qualifications

Key Competencies  

• Analytical thinking 

• Data Communication and Visualization 

• Project ownership 

• Problem solving in complexity 

Skills and Abilities  

• 6 years of professional experience in data analysis or data engineering, or 3 years with an advanced degree in GIS, geography, computer science, data science, environmental science (with a quantitative focus), or a related field. Demonstrated experience applying analytical or engineering skills in a geospatial context is strongly preferred. 

• Proficiency in data Python and/or R for data analysis and automation. Working knowledge of JavaScript for web mapping applications.  

• In day-to-day work, ability to routinely automate geospatial analyses, data processing, and reporting using tools such as ArcGIS, QGIS, Python, or others, rather than relying on manual work