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The U.S. government is closed. This site will not be updated; however, NOAA websites and social media channels necessary to protect lives and property will be maintained. To learn more, visit commerce.gov

For the latest forecasts and critical weather information, visit weather.gov.

Explore fisheries rulemaking and management in the Southeast United States (St. Petersburg, FL)

Summary / Description

The NOAA Fisheries Southeast Regional Office is responsible for protecting endangered species and marine mammals, while providing sustainable fishing opportunities in the southeast United States. This opportunity will allow an intern to contribute to the efforts of the Limited Access Privilege Programs and Data Management Branch (LAPP/DM), by helping to create new visualizations of fisheries landings data. The fishing public relies on quota tracking to determine the availability of various federally managed species, which may influence which species they target for their fishing trips. The intern will learn procedures used to track harvest of federally managed species, including the current systems for summarizing and sharing landings data with the public. The intern will become more familiar with the various management measures used to ensure sustainable harvest by both the commercial and recreational fisheries in the southeast region. Additionally, the intern will use R to create new data aggregation and visualization code via R Markdown/RShiny for key federally managed species. Strong candidates will have experience using R or other statistical analysis software to clean, manipulate, and aggregate large datasets (including creating tables and figures). Lastly, the intern will be given opportunities to conduct informational interviews and shadow available regional office staff to learn how these staff contribute to NOAA’s (social scientists, economists, regulation writers, etc).

Skills Required

  • Self-motivated, organized, and excellent attention to detail
  • Experience using R to manipulate and aggregate data (experience with R, RShiny, SAS, or other statistical software preferred).

Type of Opportunity

Location

Other Information