Job Opportunity: Quantitative Ecologist at the Audubon Society

The Audubon Society is recruiting a Quantitative Ecologist to be based either remotely or preferably out of its San Francisco office. S/He will have a PhD and a strong background in statistics and GIS. The appilcant should also know R, Python and be familiar with the mission of the National Audubon Society. The posiiton is open until filled.

Date published: 2017/08/30

As part of Audubon’s 2016-2020 Strategic Plan, the organization will focus on five core strategies: Coasts, Working Lands, Water, Climate, and Bird-friendly Communities. And, to help support the implementation of these strategies, the National Science Division applies analytical methods to guide where the on-the-ground conservation work will be most effective and rigorously measure progress as projects move forward.

As a member of this group, the Quantitative Ecologist will have responsibility for helping to conceive and execute analyses fulfilling the Division's core responsibilities. These include:

  • Developing metrics to evaluate bird response to conservation actions
  • Modeling patterns of bird abundance and distribution throughout the annual cycle and the processes that shape those patterns
  • Providing scientific justification, study design, and analyses for projects that engage the public in science
  • Supporting design and analysis of avian monitoring programs
  • Prioritizing conservation efforts

S/he will report to the Senior Quantitative Ecologist and will work closely with leadership and field teams across multiple strategies to provide critical analytical capacity that will serve as the foundation for measuring the success of Audubon’s species-focused conservation work. This position may be remotely based or embedded within one of Audubon’s state/national offices across the United States, preferably the San Francisco location.

Candidates should also submit a cover letter when applying to this position, including citations for 2-3 peer-reviewed publications and a statement on preferred work location(s).

Essential Functions:

  • Identify metrics for use in evaluating bird response to conservation actions
  • Use diverse data sets collected using a variety of protocols with varying degrees of structure to estimate population trends through space and time
  • Assist with design and analysis of avian monitoring programs
  • Analyze and prioritize conservation efforts across the Audubon network
  • Contribute to peer-reviewed publications, presentations, and grant-writing in support of projects
  • Coordinate and collaborate with Audubon staff and external partners throughout North America

Qualifications and Experience:

  • Ph.D. in ecology, biostatistics, natural resources, or other conservation- or statistics-related field required
  • Demonstrated experience applying Bayesian, frequentist, and machine learning approaches to statistical analysis of large data sets. These may include abundance, occupancy, distribution, habitat/climate/resource selection, spatial point process, demographic, population modeling, or other models implemented in a maximum likelihood or Bayesian framework (BUGS, JAGS, INLA, or STAN), using Monte Carlo simulation, or with a machine-learning algorithm such as boosted regression trees or Maxent
  • Excellent oral and written communication skills, to include a strong writing background in order to lead and co-author peer-reviewed publications
  • Demonstrated ability to clearly frame research questions, design monitoring studies, and implement analyses, as well as script analyses in R and/or Python
  • Demonstrated ability to learn and implement new quantitative approaches and think creatively about connections between birds, places, and people
  • Experience with GIS (ArcMap, QGIS, or GRASS)
  • Comfort working both independently and in a team-based environment. Passion for conservation, applied ecology and the mission of the National Audubon Society

Preferred qualifications include:

  • Familiarity with common avian data sets, protocols, and analytical methods
  • Experience in high performance computing (e.g. MCMC, STAN, JAGS, BUGS, cloud computing) and with version control software (e.g. GitHub)
  • Demonstrated ability to communicate with colleagues at all levels across the organization
  • Experience in ornithology, especially birds of North America, and/or with the birding community, including past participation in Christmas Bird Count or North American Breeding Bird Survey
  • Familiarity with Important Bird Areas or site-based conservation strategies a plus