Quantitative Analysis – Predation Modeling and Data Synthesis

Think Tank, Inc.

  • Seattle, WA
  • 30+ days ago

    Highlights

    Data compilation & spatial-temporal modeling: compile, organize, and analyze large-scale spatial and temporal datasets to evaluate effects of localized environmental conditions on predator-prey distributions and predation rates on managed fish populations. Education: Doctorate from an accredited college/university with an emphasis in a field related to the task order, including geomorphology, oceanography, hydrology, fisheries, ecology, natural sciences, mathematics, and/or statistics.

    Numbers & Facts

    LocationSeattle, WA

    Description

    *Position is Subject to Contract Award

     

    POSITION DESCRIPTION:

    Description of Duties:

    • Data compilation & spatial-temporal modeling: compile, organize, and analyze large-scale spatial and temporal datasets to evaluate effects of localized environmental conditions on predator-prey distributions and predation rates on managed fish populations.
    • Scientific communication: author technical reports and peer-reviewed journal manuscripts and present complex results at regional management meetings and scientific conferences.
    • Ecological literature reviews: summarize and document relationships between predator consumption rates, predator abundance/distribution, ecological outcomes, environmental stressors, and shifting environmental conditions.
    • Supplementary field support: physical collection of fish and environmental data (harsh outdoor conditions; may involve driving federal vehicles, boats, and trailers).
    • Data stewardship & transparency: standardize and share compiled data, workflow protocols, and research products for transparency, reproducibility, and interactivity.

     

    EDUCATION & EXPERIENCE:

    Required:

    • Education: Doctorate from an accredited college/university with an emphasis in a field related to the task order, including geomorphology, oceanography, hydrology, fisheries, ecology, natural sciences, mathematics, and/or statistics.
    • Experience: Five (5) or more years of experience related to the task order, including familiarity with the species and habitats managed by NOAA Fisheries in the West Coast region.

    Desired:

    • Advanced degree in a related field - may substitute for two (MS) or four (PhD) years of experience

     

    CERTIFICATIONS:

    Required:

    • Valid U.S. driver's license - required and maintained throughout the period of performance.
    • Public trust suitability; background investigation cleared prior to beginning performance.
    • Government-required training to be completed within 5 business days of start: NOAA IT Security, NOAA Safety, Sexual Assault/Sexual Harassment Prevention & Response (NAM 1330-52.222-70(b)(6)), and Records Management 101.

     

    RESPONSIBILITIES:

    Required (Deliverables):

    • Publications & reports: completed technical reports, peer-reviewed journal manuscripts, and/or book chapters ready for submission or publication.
    • Scientific presentations to NWFSC colleagues, regional managers, and broader scientific audiences.
    • Accessible datasets & codebases: cleaned, compiled datasets (e.g., predator diet composition, bioenergetics data, abundance indices) in organized, accessible platforms, including shared repositories (e.g., GitHub) containing datasets and analytical scripts.
    • Reproducible, fully documented analytical workflows detailed in reports, manuscripts, and version-controlled code repositories.

     

    SKILLS:

    Required:

    • Strong quantitative skills including familiarity with modeling and data analysis; familiarity with software such as R, GitHub and GIS, and with open-science concepts.
    • Excellent verbal and written communication; experience writing reports and publishing peer-reviewed articles.
    • Demonstrated ability to manage dynamic workloads, maintain high organizational standards, and deliver on time; adaptable, able to work independently in the field and within interdisciplinary teams.

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