WWF-India Recruitment | Associate Coordinator | New Delhi

Roles and Responsibilities

WWF-India is looking to recruit an individual who is trained in the ecological sciences – and highly skilled in computer programming, statistics and spatial analysis – to support data aggregation and synthesis to devise and assess conservation interventions. By developing and operationalizing cutting-edge and data-driven solutions to enhance programmatic efficiency and drive evidence-based conservation, applicants will be encouraged to devise ways of bringing large and complex socio-ecological datasets together.

This role will also entail design and contribute to project design field data collection in multiple conservation landscapes, collaboratively developing research and conservation project proposals, team management, and providing science support by building capacities of WWF India’s field teams for data operations.

As WWF India’s Wildlife and Habitats division transitions to more sophisticated data management systems, the person appointed to this position will also need to contribute to developing and operationalizing these systems and associated protocols.

Location: New Delhi

Technical:

Steer WWF’s engagement in the following:

Support the design, development and operationalization of an end-to-end data management system for the Wildlife and Habitats division of WWF India to archive and integrate diverse data sets, with a focus on camera trap data from the tiger program. Co-maintain a data-management dashboard.
Support the development of apps and software for efficient data collection and M&E related to corridors and human wildlife conflict
Support data analysis and report/ paper writing for select projects from the landscape/ synthesis analyses, and provide analysis support for other initiatives.
Support the development of a dashboard for tiger population recovery
Co-design conservation projects in the landscapes to better integrate social and ecological datasets with biologists and community-team program members.
Contribute to the development, periodic revision and implementation of strategy for the tiger conservation program, and actively build synergies for data components snow leopard, elephant and rhino conservation programs

Networking, Coordination and Communication:

Maintain a dashboard of key tiger-conservation initiatives across landscape and communicate updates to the senior management team with inputs form the landscapes
Play a key role in the development of internal and external statements, reports and peer-reviewed publications arising from the tiger landscapes or broader initiatives
Regularly communicate information on key (tiger) conservation initiatives to the broader public
Coordinate data management related initiatives across the tiger landscapes.

Program Development:

Co-develop proposals, especially for data management and synthesis and support the development of other relevant proposals
Contribute to the development of data management policies sand workflows
Enable effective data management and analysis in the landscape by leading or facilitating workshops

Qualifications, Experience and competencies required:

MSc or PhD in Wildlife Science, Ecology, Conservation Biology or allied disciplines with a specialization in population ecology, landscape ecology, spatial analysis and familiarity with social-science methods.
Familiarity with sampling design for wildlife and habitat monitoring; training in statistics (at least two semesters at the graduate level), familiarity with Bayesian analyses and MCMC methods; one or more semesters of coursework (or on the job experience) in GIS and geospatial analyses using remotely sensed data; programming skills in R, Python, Linux Terminal Tools, JavaScript including applications in Google Earth Engine, HTML, C++, R, SQL Technology Linux OS, Git
Additional experience with spatial conservation prioritization tools (Zonation, MarXan, C-Plan) and social science methods (Atlas/ Envivo)
Proven proficiency in ecological modeling in the form of relevant publications, or at least two years of professional experience in data analysis and modeling

Education: