Sustainability Data Analyst, Worldly

• The ideal candidate is detail-oriented and curious, a self-starter who enjoys understanding how calculations work, validating assumptions, and ensuring that outputs are reliable and defensible. This is a hands-on role for someone who enjoys balancing deep independent work with highly collaborative cross-functional stakeholder engagement
• Exceptional attention to detail and a strong desire to understand how data and calculations work from end-to-end
• Bachelor's degree or similar experience in a relevant field (e.g., Sustainability, Environmental Engineering, Data Science)
• 2+ years of experience working in an analytical, data-focused, or consulting role
• Strong proficiency in SQL and comfort working directly with raw data
• Solid understanding of sustainability concepts, such as environmental impact measurement or carbon accounting
• Ability to work independently, manage priorities, and move work forward with minimal oversight
• Strong problem-solving skills and persistence when working through complex or ambiguous data challenges
• Clear written and verbal communication skills for both technical and non-technical audiences
• Comfort working cross-functionally and incorporating feedback from multiple stakeholders
• Claude/AI fluency

Desirable

• Worldly is seeking a Sustainability Data Analyst with a passion for deep, detailed work with complex data. This person will partner with teams across Worldly to ensure the accuracy, consistency, and integrity of the sustainability data we provide to customers
• Work directly with large, complex sustainability datasets to support the development and maintenance of Worldly’s impact content
• Conduct content quality assurance (QA) and user acceptance testing (UAT) for sustainability calculations, metrics, and related content to ensure product and data accuracy and consistency across the Worldly platform
• Update and maintain complex assessment-defining files based on specifications from stakeholders
• Manage analytical content that controls and governs customer data exports
• Investigate and resolve data issues and questions by tracing outputs back to the source data and underlying logic
• Query Worldly data with SQL to support internal and external customer needs
• Collaborate cross-functionally with product, engineering, and customer-facing teams to align data outputs that meet platform needs and customer expectations
• Continuously improve automation, documentation, and internal understanding of calculations, metrics, and data structures
• Conduct targeted research projects