Senior Analyst - National Characterization
New
C
Circular Action AllianceEnvironmental Science
Remote from the United States of AmericaFull-TimeSenior
Salary107,000 - 127,000 USD per year
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Job Details
- Experience
- 7–10 years
- Required Skills
- PythonData AnalysisMicrosoft ExcelData visualizationR
Requirements
- Bachelor’s degree required; Master’s degree in Environmental Science, Engineering, Waste Management, Data Analytics, or a related field preferred.
- 7–10 years of experience in waste characterization, recycling, materials management, or environmental data analysis.
- Advanced proficiency in Python and/or R for data management, statistical analysis, and reproducible analytical workflows.
- Advanced Microsoft Excel skills.
- Strong knowledge of waste characterization methodologies, material classification systems, and performance metric development (e.g., contamination, capture, and recycling rates).
- Experience overseeing large, complex datasets and implementing data governance and QA/QC practices.
- Experience developing standard operating procedures (SOPs) and governance frameworks.
- Knowledge of extended producer responsibility (EPR) programs and related policy frameworks.
- Demonstrated ability to translate technical analyses and methodologies into clear recommendations.
- Strong project leadership and stakeholder management skills.
Responsibilities
- Lead the development, implementation, and continuous improvement of processes governing the intake and integration of waste characterization datasets.
- Oversee data quality assurance activities, including the standardization, validation, and preparation of characterization data for incorporation into CAA systems.
- Lead the development and ongoing refinement of national sort category frameworks and category mapping methodologies.
- Direct comparative and trend analyses to identify emerging patterns and support cross-state benchmarking.
- Oversee the development of analytical summaries, data visualizations, and reporting deliverables for internal and external stakeholders.
- Establish and maintain QA/QC frameworks, validation standards, and acceptance criteria.
- Partner with the Data & Analytics team to ensure characterization data structures support enterprise architecture.
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