Role Description The contractor shall perform the following tasks: - Support the fishery management actions necessary to enable rapid fulfillment of the requirements of the Seafood Executive Order. - Support the economic analysis for fisheries management actions resulting from the Seafood EO, including but not limited to: - Conducting Regulatory Impact Review analyses. - Developing fishery descriptions. - Conducting Regulatory Flexibility Analysis reviews (including Section 610 reviews). - Conducting Small Business entity analyses. - Assessments including, but not limited to, cost-benefits of proposed management options, addressing: - Fisheries bycatch and discard issues. - Capacity. - Protected species issues. - Habitat protection restrictions. - Social impact assessments. - Provide fisheries management input to the Office of Science & Technology’s Trade Dashboard in support of the Seafood EO. - Evaluate the effects of allocation options between commercial and recreational sectors; within sectors. - Evaluate surveys and research of socioeconomic impacts of management actions and disasters on fishing communities, including: - General public. - Fishing businesses. - Crew. - Aquaculture operations. - Marine-related businesses. - Seafood-business employees. - Evaluate comparative analyses of fishing labor trends. - Technical editing of economic input to fishery management actions in support of the Seafood EO. - Evaluation of decision support tools, including: - Bio economic models. - Integrated ecosystem models. - Angler behavioral models. - Seafood markets and trade. - Aquaculture. - Fisheries economic impact models. - Provide support for socio-economic analyses for fisheries management actions for which NOAA is responsible. Deliverables The contractor shall submit the following deliverables under Task 2: - Economic analyses for fishery management actions. - Progress report including: - Accomplishments. - Issues encountered. - Travel (including purpose, significant outcomes, action items). - Recommendations, if applicable. - Trade Dashboard Data & Technical Inputs: Validated economic data sets and analytical summaries provided to the Office of Science & Technology to populate the Seafood EO Trade Dashboard. - Regulatory Impact Review (RIR) & Regulatory Flexibility Analysis (RFA) Reports: Comprehensive analysis of the economic costs, benefits, and impacts of proposed fishery management actions on small business entities (vessels, processors, and aquaculture). - Socio-Economic Impact Assessments (SIA): Detailed reports quantifying the effects of management options on fishing communities, including data on labor trends, crew participation, and impacts on marine-related businesses and the general public. - Fishery Management Action Technical Edits: Polished economic sections within larger fishery management documents, ensuring all inputs meet NOAA/NMFS leadership standards for clarity and statutory compliance. Qualifications - Experience in economic analysis related to fisheries management. - Strong analytical skills and attention to detail. - Ability to work independently in a remote environment. Requirements - Full-Time employment. - Remote position. Benefits - 401(k) - Competitive salary - Dental insurance - Health insurance - Vision insurance

• Gather, analyze and document business and data requirements from stakeholders across enterprise domains • Manage and prioritize incoming data-related requests, tickets and business needs • Translate business requirements into clear data requirements to support ingestion and transformation processes • Support the development and expansion of enterprise-level data products and gold-layer datasets • Collaborate with data architects, engineers and delivery leads to ensure alignment between business objectives and technical solutions • Collect and document data quality rules, metadata and catalog descriptions for new data ingestions • Work with governance and stewardship teams to support data lineage, quality and cataloging initiatives • Facilitate communication between business stakeholders and technical delivery teams • Contribute to continuous improvement initiatives across data delivery and operational processes • Support Agile ceremonies, backlog refinement and workflow management activities • Participate in cross-functional discussions related to data modeling, transformation logic and platform capabilities

• Lead and support end-to-end analytics processes including data acquisition, transformation, analysis, and reporting. • Manage and optimize data workflows within the Databricks platform to improve efficiency, performance, and cost management. • Analyze key business performance metrics such as CTP, CVR, engagement, and funnel performance to identify trends and optimization opportunities. • Investigate data trends, user behavior, and performance issues to identify root causes and recommend solutions. • Translate analytical findings into clear business requirements for A/B testing, funnel optimization, and product improvements. • Collaborate with data engineering and cross-functional teams to resolve data discrepancies and ensure data accuracy across systems. • Document business and technical requirements for roadmap initiatives, data tagging enhancements, and technical refresh projects. • Support strategic planning for data initiatives, including KPI tracking, reporting, and performance measurement. • Work closely with stakeholders to align analytics solutions with business goals and priorities.

• Analyze large-scale datasets related to agent performance, support interactions and QA. • Write optimized SQL queries using tools like **BigQuery** and **ClickHouse**. • Build dashboards in **Tableau**, **Metabase**. • Detect behavioral and performance trends among agents and support teams. • Partner with QA to identify root causes in agent behavior and customer issues. • Use LLM tools with practical **prompt engineering** for daily analytical tasks, summarization, and insights generation. • Ability to assess and profile LLM outputs for quality, relevance, and analytical correctness in business contexts. • Familiarity with **LLM APIs** and integrating model outputs into analytical or internal tooling workflows. • Work with Airflow and Python to automate data tasks and support workflows. • Optimize analytics pipelines and data marts to improve performance, resource efficiency, and reliability. • Identify and refactor inefficient DAGs, queries, and transformations to ensure scalable and cost-effective data processing. • Suggest and co-build improvements in agent tooling, ticket routing, and SLA tracking. • Translate business inefficiencies into trackable metrics and measurable outcomes. • Act as an analytical partner to **Operations**, **Support Management**, **QA**, and **Training**. • Work with **Data Engineering** to ensure clean, accurate, and well-modeled data pipelines. • Communicate findings clearly through presentations, visualizations, and concise documentation.