Azura is looking for an experienced R programmer to develop a unified tool for generating design-based estimates of cetacean abundance. This work will be conducted for NOAA Fisheries in the Pacific, and the tool should be easily adapted for use by analysts in other regions.
This project will involve updating and transitioning the existing analysis code into an open data science format using R and related tools (e.g., RStudio, R Markdown, Git, GitHub). The core components of the abundance estimation tool include data processing, data evaluation, detection function formulation, and parameter estimation for two specific methods: 1) a group-based application for most species where the estimator accounts for the effect of multiple covariates on the detection function and 2) a subgroup-based application for false killer whales where the estimator allows for separate estimation of each parameter. The final product from this effort will be the streamlined and well-annotated code and associated documentation that users can access through GitHub although the feasibility and utility of R packaging may also be considered.
- Update and transition existing code for each core component of each design-based abundance estimation method (i.e., group-based for most species and subgroup-based for false killer whales) into an open data science format using the R programming language and related tools.
- For the data processing component, develop new code that refines output from the newly developed R package ‘swfscDAS’, which processes data files from the line-transect data collection program ‘WinCruz’, and produces sightings and effort summaries in formats needed for evaluation and analysis.
- For the data evaluation component, develop new code that uses the processed sightings summary and examines data availability by cetacean species and stock, truncation distances for detection functions, and sample sizes for detection function and abundance estimation.
- For the detection function formulation component, develop new code that uses the processed sightings summary and established truncation distances and models and evaluates each detection function, interfacing with existing ‘Distance’ R packages when possible.
- For the parameter estimation component, develop new code that uses the processed data summaries and detection function models and estimates the survey-specific parameters and results (i.e., effective strip width, group or subgroup size, trackline detection probability or g(0), density, and abundance) and associated uncertainty using established bootstrap procedures.
- Annotate and debug the new code and work with NOAA to validate the results of each core component for each method.
- Ensure that the new code is integrated across all components and, to the extent possible, generalized for each method so that the abundance estimation tool can be implemented for multiple species and stocks at one time.
- Work with NOAA to prepare any additional documentation that may be required to package, publish, or otherwise distribute the abundance estimation tool.
- Interpreting code written by others in the R programming language
- Creating efficient and streamlined R code in an open data science format
- Using open data science tools, such as the R package ‘tidyverse’, RStudio, R Markdown, Git, and GitHub
- Proficiency with developing R code for quantitative and statistical analyses
- Ability to create code in a collaborative environment with feedback and collaboration during the development and validation process
- Excellent verbal and written communication skills
- Interpreting code written by others in the Fortran programming language
- Familiarity with design-based line-transect analysis
Work will be conducted remotely, and you must be able to pass a security background check. If you are interested in this position and have all of the required qualifications listed above, please send your resume and cover letter to firstname.lastname@example.org. In your resume, please describe how you meet all of the required qualifications and list contact information for three references who can attest to your previous work experience. In your cover letter, please describe why you would be a good fit for this position.
Azura Consulting LLC is an Equal Opportunity Employer and does not discriminate on the basis of any status or condition protected by applicable federal or state law. We strongly encourage all qualified persons to apply for this position.