Distance Sampling Data Analyst: Remote/Woods Hole, MA

Integrated Statistics, Inc
Remote/Woods Hole, MA
Job Category
Full time Positions
Commensurate with experience and qualifications
Start Date
Last Date to Apply
Integrated Statistics is looking for a Distance Sampling Data Analyst to support the National Oceanic and Atmospheric Administration (NOAA) National Marine Fishery Service (NMFS) Northeast Fisheries Science Center (NEFSC). The Distance Sampling Data Analyst will assist NEFSC's Protected Species Branch (PSB) with the analysis of two disparate types of data on marine mammal distributions. PSB's mission includes assessing the population status of protected species (cetaceans, sea turtles, seabirds, and seals) within U.S. waters, and evaluating threats to species and populations due to anthropogenic activities. Detailed assessments of species distributions and abundances are essential to understand broad scale spatial and temporal movements and behaviors. For risk assessment and mitigation of impacts, information on seasonal and inter-annual variability in distribution, ecology, and behavior at smaller spatial scales is used to estimate potential impacts on protected species due to localized activities (e.g., fishery bycatch, military exercises, energy exploration, shipping traffic, etc.). The objective of this one-year study is to compare high-resolution aerial imagery survey and visual survey methodologies from marine mammal line transect surveys conducted over the New York Bight. The reason for the comparison is to explore avenues to integrate data from both data streams to be able to create a consistent time series of aerial survey data results from both imagery and visual data. The line-transect survey data comes from two main sources: traditional visual aerial survey effort; and digital aerial survey effort using high-definition cameras. A third source, visual 2-team visual aerial survey efforts conducted by NMFS, may augment the main two data sources. Duties The project tasks include: Processing the data from two main sources to allow comparison of these two datasets. Conducting summary analyses of the datasets, modelling the datasets, and evaluating assumptions of the analyses and modeling. Comparing the results from the two data sources. Developing a report or peer-reviewed journal paper of the methods used and results. The analyses include, but are not limited to, developing general spatiotemporal summaries of the raw data. The modeling includes, but is not limited to, developing spatiotemporal distribution and abundance maps and estimates using Distance sampling methods. Results from the two datasets should be compared using appropriate statistical evaluation.
Qualifications and Skills The successful candidate should possess: A Master's or PhD in a biological field of study that included statistical and programming coursework, or equivalent. Expertise in using the R software, with these specific skill sets: Manipulating large datasets. Conducting statistical evaluations. Analyzing line-transect data using the Distance R packages such as mrds. Fitting density surface models to line-transect data using R packages such as dsm, mgcv, etc. Track record of success in working independently within a team environment, with limited supervision. Demonstrated ability to develop timely reports or journal papers documenting scientific results. Excellent written and oral communication skills. Ability to adapt quickly to changing priorities and strict timelines. US citizenship and presence. Ability to comply with EO 14042. The position is expected to last one year. The position may be filled remotely within the US, with the ability to travel to Woods Hole, MA for meetings. The rate of pay will depend on skills and experience, and the position is eligible for the benefits described on the Integrated Statistics website. To apply for this position, go to https://jobs.intstats.com/JobDetails.jsp?jobListingId=297 or visit www.integratedstatistics.com, click Employment Opportunities, click the job name and click the Apply Here link. Integrated Statistics is an equal opportunity employer and will not discriminate against any employee or applicant on the basis of age, color, disability, gender, national origin, race, religion, gender identity, sexual orientation, veteran status, or any classification protected by federal, state, or local law. Consistent with its obligations under federal law, Integrated Statistics is committed to taking affirmative action to employ and advance in employment qualified women, minorities, disabled individuals, special disabled veterans, veterans of the Vietnam era, and other eligible veterans. For assistance with accessibility of applications, posters, forms, and/or documents, please email the Integrated Statistics office.
Contact Person
Dr Laura Shulman
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