Senior Analyst - National Characterization

Circular Action Alliance• Remote, US,

3d•$75,000 - $90,000•Remote

About The Position

The National Senior Characterization Analyst provides leadership for the acquisition, stewardship, analysis, and reporting of material characterization data across CAA states. This role establishes and maintains national standards for data quality, consistency, and comparability, ensuring characterization datasets support organizational reporting, strategic planning, and program evaluation. As the primary authority on characterization data governance, the position oversees the integrity and long-term usability of data generated through CAA characterization studies. The Senior Analyst will be on the Collection & Processing team within the Material Services department of Program Planning and Operations (PPO), which also includes Data & Analytics, Compliance & Regulatory Affairs, and Emerging States. This position leads the development and maintenance of sort category frameworks across states, including the alignment of study-specific sort categories with state reporting requirements. The role evaluates waste characterization studies conducted by states and local jurisdictions to assess methodological alignment and opportunities for integration into CAA programs. The National Senior Characterization Analyst provides strategic oversight and guidance to CAA state teams to address data quality concerns, promote standardized practices, and ensure consistency with both national objectives and state-specific requirements. In partnership with the CAA Data & Analytics team, this role oversees the integration of characterization data into enterprise data structures and analytical frameworks, ensuring data assets effectively support organizational reporting and decision-making needs. The position is responsible for establishing, maintaining, and continuously improving standard operating procedures related to data intake, quality assurance and quality control, data management, and long-term data governance, reinforcing accountability, consistency, and data integrity across characterization programs.

Requirements

Strong understanding of waste characterization and materials management concepts, including contamination, capture, and recycling rate methodologies and the assumptions underlying their application.
Advanced proficiency in Python and/or R for data management, transformation, statistical analysis, automation, and development of reproducible analytical workflows.
Demonstrated ability to develop and communicate data-driven insights through effective visualizations, dashboards, and technical reporting.
Experience designing, implementing, and overseeing QA/QC frameworks for complex, multi-source datasets to ensure data integrity and defensibility.
Strong technical writing skills, including the development and maintenance of SOPs, governance frameworks, data standards, and analytical documentation.
Ability to communicate complex analytical concepts, data limitations, and quality findings to both technical and non-technical audiences.
Proven ability to build and maintain collaborative relationships across departments and organizations to advance data quality, consistency, and reporting objectives.
Working knowledge of extended producer responsibility (EPR) programs and related policy, regulatory, and reporting frameworks.
Demonstrated ability to prioritize and oversee multiple projects, initiatives, and stakeholder needs in a dynamic environment
Strong attention to detail and commitment to data accuracy, consistency, and continuous improvement.
Ability to operate independently, exercise sound professional judgment, and proactively identify and escalate risks and issues when appropriate.
Bachelor’s degree required; Master’s degree in Environmental Science, Engineering, Waste Management, Data Analytics, or a related field preferred.
7–10 years of progressively responsible experience in waste characterization, recycling, materials management, environmental data analysis, or related fields, including leadership of complex data initiatives and cross-functional stakeholder engagement.
Demonstrated expertise with data analysis, management, and reporting tools, including advanced proficiency in Python and/or R. Advanced Microsoft Excel skills required. Experience developing scalable, reproducible analytical workflows preferred.
Experience overseeing large, complex datasets and implementing data governance, QA/QC, and quality management practices to ensure data integrity, consistency, and defensibility.
Strong knowledge of waste characterization methodologies, material classification systems, and performance metric development, including contamination, capture, and recycling rate calculations.
Proven ability to translate technical analyses, methodologies, and data limitations into clear recommendations and guidance for diverse internal and external stakeholders.
Experience developing standards, SOPs, governance frameworks, or data management practices that support organizational consistency and long-term data stewardship.
Strong project leadership, organizational, and stakeholder management skills, with the ability to balance multiple priorities while advancing strategic program objectives.

Nice To Haves

Master’s degree in Environmental Science, Engineering, Waste Management, Data Analytics, or a related field preferred.
Experience developing scalable, reproducible analytical workflows preferred.

Responsibilities

Lead the development, implementation, and continuous improvement of processes governing the intake and integration of waste characterization datasets, including new studies, legacy datasets, third-party data, and state-generated studies.
Oversee data quality assurance activities, including the standardization, validation, and preparation of characterization data for incorporation into CAA systems and analytical platforms.
Establish and maintain standards for metadata management, documentation, dataset assumptions, and version control to ensure transparency, consistency, and long-term data integrity.
Lead the development, implementation, and ongoing refinement of national sort category frameworks, ensuring consistent application across CAA programs, state initiatives, and pilot studies.
Provide oversight of category mapping methodologies, addressing state-specific reporting requirements, category discrepancies, and study-level variations to maintain data comparability and analytical consistency.
Evaluate state and local waste characterization studies to assess methodological alignment, data suitability, and opportunities for integration into CAA characterization programs and reporting efforts.
Provide leadership for the development and application of analytical methodologies used to calculate key CAA performance metrics, including contamination, capture, and recycling rates, leveraging validated characterization datasets.
Direct comparative and trend analyses to identify emerging patterns, support cross-state benchmarking, and inform programmatic decision-making.
Oversee the development of analytical summaries, data visualizations, and reporting deliverables that support internal stakeholders, strategic initiatives, and external reporting requirements.
Establish and maintain QA/QC frameworks, validation standards, and acceptance criteria to ensure the defensibility, consistency, and reliability of characterization datasets across studies.
Provide strategic guidance and oversight to CAA state teams in the resolution of data quality and reporting issues, promoting alignment with national standards and best practices.
Partner with the CAA Data & Analytics team to ensure characterization data structures, classifications, and workflows support enterprise data architecture, reporting objectives, and analytical needs.
Lead the development, implementation, and continuous improvement of SOPs governing data intake, QA/QC, category management, analytical methodologies, and long-term data governance practices.
Other job duties as assigned.