LCA Analyst (Life Cycle Assessment)

Remote
Full Time
Mid Level
Position Description: Experienced professionals in life cycle assessment (LCA), with preferably, but not necessarily, a focus on electronics, textile/fashion or agricultural supply chains. These individuals will be responsible for working with some of the largest organizations in the world to translate operational and supply chain data into detailed LCA models that help these organizations assess sustainability-related risks, report on corporate goals and identify promising initiatives to reduce environmental impacts. Highly collaborative positions involving finance, data science and software teams.

Education: Master’s or PhD in industrial ecology or a similar engineering or other sustainability-related degree with a heavy focus on life cycle assessment methods. Bachelor will be considered if candidate has demonstrated subject matter expertise and at least five (5) years of experience.

Qualifications:
  1. Educated and experienced in the computational elements of life cycle assessment such as:
    1. Co-product allocation rules
    2. Data normalization
    3. Underlying matrix computations used to derive inventory and impact results
    4. Uncertainty and sensitivity analyses
  2. Proven experience building life cycle inventories, including:
    1. Data collection methods (e.g., survey design and deployment)
    2. Model development, with focus on process-based
  3. Experience completing LCAs compliant with ISO 14040 and 14044 and ILCD International Life Cycle Data system publications.
  4. Expertise in life cycle impact assessment methods, with emphasis on spatially explicit models.
  5. Content-specific knowledge/experience with electronics, textile/fashion or agricultural LCAs
  6. Excellent problem-solving capabilities
  7. Entrepreneurial mindset, eager to learn new fields and grow with the company

Nice to have skills:
  1. Project management training/experience
  2. Experience with hybrid LCA models
  3. Life cycle inventory database development/curation/maintenance
  4. Experience with GIS and spatial analytics
  5. Programming experience, especially with R, Python and SQL
  6. Experience with data visualization platforms (e.g., PowerBI)
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