https:\/\/www.quinaultindiannation.com\/DocumentCenter\/View\/105\/QIN-Employment-Application-PDF?bidId=<\/a>)<\/p>\n\u00a0<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
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MINIMUM QUALIFICATIONS \u2013<\/h2>\n
Bachelor\u2019s degree in Fisheries Science, Marine Biology, Quantitative Ecology, Biostatistics, or a related field and at least one year of experience in fisheries stock assessment, population dynamics modeling, or quantitative analysis of marine ecological data.<\/p>\n
The Quinault Indian Nation is seeking a dedicated and experienced Fisheries Biometrician to join our Quinault Department of Fisheries team. The Fisheries Biometrician plays a crucial role in the assessment, management, and conservation of Quinault fisheries resources by applying statistical methods and modeling techniques to fisheries data. The individual will collaborate with multidisciplinary teams within and outside of the Quinault Department of Fisheries to analyze population dynamics, evaluate fishing practices, and inform sustainable management strategies. The ideal candidate will have a strong background in fisheries science, quantitative analysis, and statistical modeling, along with a passion for sustainable fisheries and ecosystem management.<\/p>\n
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JOB DUTIES INCLUDE \u2013<\/h2>\n
\u00b7 Data Analysis and Modeling: Conduct statistical analyses of marine and freshwater<\/p>\n
fisheries data, including stock assessments, catch and effort data, biological samples, and environmental variables. Develop and apply mathematical models to estimate population parameters, assess fishery dynamics, and forecast future trends.<\/p>\n
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\u00b7 Stock Assessment: Implement methodologies for estimating fish stock abundance, biomass, growth rates, mortality rates, and recruitment patterns using age-structured, length-structured, or spatially explicit models.<\/p>\n
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\u00b7 Fishery Management Support: Provide scientific advice and technical support to Quinault Fisheries staff and policy representatives, tribal fishermen and public. Collaborate with tribal, state and federal management agencies on co-managing fisheries. Evaluate the effectiveness of management measures including catch quotas, size limits, and spatial closures, in achieving sustainability objectives.<\/p>\n
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\u00b7 Data Integration and Synthesis: Integrate data from multiple sources, including fishery-independent surveys, commercial landings, observer programs, and ecosystem indicators, to develop holistic assessments of fishery status and ecosystem health.<\/p>\n
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\u00b7 Risk Assessment and Decision Analysis: Assess the potential impacts of alternative management scenarios on fish stocks, marine ecosystems, and socio-economic outcomes. Conduct risk analyses and decision analysis frameworks to inform adaptive management strategies and policy decisions.<\/p>\n
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\u00b7 Communication and Collaboration: Collaborate with fisheries scientists, biologists, economists, and stakeholders to communicate research findings, present technical information, and facilitate stakeholder engagement processes. Contribute to scientific publications, reports, and presentations for both technical and non-technical audiences.<\/p>\n
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\u00b7 Capacity Building and Training: Provide training and mentorship to junior staff, students, and partner organizations on statistical methodologies, modeling techniques, and best practices in fisheries science and management.<\/p>\n
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EXPERIENCE, KNOWLEDGE, SKILLS \u2013<\/h2>\n
Required Qualifications \u2013 (Level Professional 5 \/ Grade 11)<\/p>\n
\u00b7 Bachelor\u2019s degree in Fisheries Science, Marine Biology, Quantitative Ecology, Biostatistics, or a related field.<\/p>\n
\u00b7 Minimum three years\u2019 experience in fisheries stock assessment, population dynamics modeling, or quantitative analysis of marine ecological data.<\/p>\n
\u00b7 Demonstrated experience in statistical software packages such as R, Stock Synthesis, AD Model Builder, or similar tools for conducting Bayesian and frequentist analyses.<\/p>\n
\u00b7 Strong understanding of fisheries biology, population dynamics, and ecosystem interactions, including knowledge of fish life history traits, recruitment processes, and habitat preferences.<\/p>\n
\u00b7 Familiarity with fishery management concepts, regulatory frameworks, and international agreements governing sustainable fisheries, such as the Pacific Salmon Treaty and the Magnuson-Stevens Act.<\/p>\n
\u00b7 Excellent analytical skills, critical thinking abilities, and attention to detail, with the ability to synthesize complex datasets and communicate results effectively.<\/p>\n
\u00b7 Strong interpersonal skills and the ability to work collaboratively in multidisciplinary teams, fostering positive relationships and contributing to a culture of scientific<\/p>\n
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Required Qualifications \u2013 (Level Professional 5 \/ Grade 12)<\/h2>\n
\u00b7 Bachelor\u2019s degree in Fisheries Science, Marine Biology, Quantitative Ecology, Biostatistics, or a related field.<\/p>\n
\u00b7 Minimum five years\u2019 experience in fisheries stock assessment, population dynamics modeling, or quantitative analysis of marine ecological data.<\/p>\n
\u00b7 Master\u2019s degree may substitute for two years of experience.<\/p>\n
\u00b7 Demonstrated experience in statistical software packages such as R, Stock Synthesis, AD Model Builder, or similar tools for conducting Bayesian and frequentist analyses.<\/p>\n
\u00b7 Strong understanding of fisheries biology, population dynamics, and ecosystem interactions, including knowledge of fish life history traits, recruitment processes, and habitat preferences.<\/p>\n
\u00b7 Familiarity with fishery management concepts, regulatory frameworks, and international agreements governing sustainable fisheries, such as the Pacific Salmon Treaty and the Magnuson-Stevens Act.<\/p>\n
\u00b7 Excellent analytical skills, critical thinking abilities, and attention to detail, with the ability to synthesize complex datasets and communicate results effectively.<\/p>\n
\u00b7 Strong interpersonal skills and the ability to work collaboratively in multidisciplinary teams, fostering positive relationships and contributing to a culture of scientific excellence and innovation.<\/p>\n
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Required Qualifications \u2013 (Level Professional 6 \/ Grade 13)<\/h2>\n
\u00b7 Bachelor\u2019s degree in Fisheries Science, Marine Biology, Quantitative Ecology, Biostatistics, or a related field.<\/p>\n
\u00b7 Minimum seven years\u2019 experience in fisheries stock assessment, population dynamics modeling, or quantitative analysis of marine ecological data.<\/p>\n
\u00b7 Master\u2019s degree may substitute for two years of experience.<\/p>\n
\u00b7 Demonstrated experience in statistical software packages such as R, Stock Synthesis, AD Model Builder, or similar tools for conducting Bayesian and frequentist analyses.<\/p>\n
\u00b7 Strong understanding of fisheries biology, population dynamics, and ecosystem interactions, including knowledge of fish life history traits, recruitment processes, and habitat preferences.<\/p>\n
\u00b7 Familiarity with fishery management concepts, regulatory frameworks, and international agreements governing sustainable fisheries, such as the Pacific Salmon Treaty and the Magnuson-Stevens Act.<\/p>\n
\u00b7 Excellent analytical skills, critical thinking abilities, and attention to detail, with the ability to synthesize complex datasets and communicate results effectively.<\/p>\n
\u00b7 Strong interpersonal skills and the ability to work collaboratively in multidisciplinary teams, fostering positive relationships and contributing to a culture of scientific excellence and innovation.<\/p>\n
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DESIRED EXPERIENCE, KNOWLEDGE, SKILLS \u2013<\/h2>\n
\u00b7 Experience with advanced modeling techniques, such as state-space models, integrated assessment models, or spatially explicit models for fisheries management.<\/p>\n
\u00b7 Knowledge of data-limited methods for assessing fisheries status and setting harvest control rules in the absence of detailed biological information.<\/p>\n
\u00b7 Experience with programming languages such as Python, MATLAB, or Julia for data manipulation, simulation, and model development.<\/p>\n
\u00b7 Demonstrated track record of publications in peer-reviewed journals or contributions to<\/p>\n
fisheries assessments and management plans.<\/p>\n
\u00b7 Experience working with stakeholders, indigenous communities, or fishery advisory councils to incorporate traditional knowledge and local perspectives into management decisions.<\/p>\n
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HYBRID WORK OPTION \u2013<\/h2>\n
The candidate will be allowed to work remotely when feasible but must visit worksites, partner and agency offices and scheduled, in-person meetings as required. Virtual meetings are encouraged for technical and logistical discussions and when in-person attendance is not required. The position must be available to visit and work from the Quinault Administration Complex in Taholah, Washington as required to meet the obligations of updating and receiving direction from supervisors, policy bodies and leadership of the Quinault Indian Nation. The position will have an office assigned at the Quinault Department of Fisheries for hybrid or full-time use.<\/p>\n
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PHYSICAL REQUIREMENTS \u2013<\/h2>\n
This position requires the ability to work at a desk with computers and mobility to collaborate with others as needed. Optional field visits are encouraged to view fishery locations, techniques, and sampling methodologies.<\/p>\n
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OTHER REQUIREMENTS \u2013<\/h2>\n
\u00b7 Must have a valid Washington State Driver\u2019s license or be able to obtain one within the first month of employment.<\/p>\n
\u00b7 Must have and maintain the ability to be insured under the Quinault Indian Nation automobile insurance.<\/p>\n
\u00b7 Must be able to maintain confidentiality of information.<\/p>\n
\u00b7 Able to comply with the Federal Drug Free Workplace Act.<\/p>\n
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BENEFITS \u2013<\/h2>\n
\u00b7 Very competitive Medical\/Dental Plans.<\/p>\n
\u00b7 Generous Paid Time Off including Annual Leave and over 20 paid Holidays. 12 days of Annual Leave accrued in first full year of employment.<\/p>\n
\u00b7 Generous Sick Leave accrual.<\/p>\n
\u00b7 401K and Profit Sharing after one year of employment including matching contributions by employer.<\/p>\n
\u00b7 Wellness Leave time.<\/p>\n
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How to Submit Applications \/ Contact Us<\/h2>\n
Contact Jobs@quinault.org or call (360) 276-8211 ext. 4600 for information regarding job openings.<\/p>\n
For information specific to the position contact Joe Schumacker, jschumacker@quinault.org or call (360) 276-8211 ext. 7327. \u00b7 QIN Application (PDF) (https:\/\/www.quinaultindiannation.com\/DocumentCenter\/View\/105\/QIN-Employment-Application-PDF?bidId=)<\/p>\n
If you have a current application on file, you can also call (360)-276-8211 ext. 4618. To ask that your application be submitted for the position by the COB of closing date.<\/p>\n\n\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":10410,"featured_media":34097,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_s2mail":"yes"},"categories":[14,15,210],"tags":[4,559,456,7960,5898,7963,32,33,350,7965,7,7962,7964,7961,6768,6658],"_links":{"self":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts\/54919"}],"collection":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/users\/10410"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/comments?post=54919"}],"version-history":[{"count":1,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts\/54919\/revisions"}],"predecessor-version":[{"id":54920,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts\/54919\/revisions\/54920"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/media\/34097"}],"wp:attachment":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/media?parent=54919"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/categories?post=54919"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/tags?post=54919"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}