About this Job
EcoRatings is seeking a detail-oriented Sustainability & ESG Data Research Analyst to build the critical knowledge foundation that powers our flagship AI product — EcoRatingsOS.
As a core member of the Data track, you will bridge the gap between the vast and fragmented ESG data landscape and our generative AI models. This role is ideal for a researcher who combines deep sustainability domain knowledge with a technical, rigorous, data-driven mindset and thrives on solving complex data sourcing challenges in a fast-moving product environment.
Responsibilities
- Data Research & Sourcing: Identify, evaluate, and catalog sustainability and ESG-focused datasets from global data providers, regulatory bodies, NGOs, satellite feeds, financial data vendors, and open-data repositories — assessing each for quality, coverage, freshness, and licensing suitability.
- Standards & Regulatory Monitoring: Track evolving ESG disclosure frameworks (CSRD, TCFD, GRI, ISSB, SEC climate rules) and emerging data categories (nature-related risk, scope 3 supply chain emissions, just transition metrics) to keep EcoRatingsOS aligned with the latest standards.
- Product Collaboration: Partner with AI Engineers, Data Engineers, and the Product Lead to translate research findings into structured data schemas, feature specifications, and ingestion requirements for the EcoRatingsOS intelligence layer.
- Agentic Architecture Support: Collaborate with the AI Agentic Architecture team to inform the design of autonomous data-collection agents — defining source lists, data contracts, scope, and refresh cadences.
- Data Quality & Governance: Design and apply systematic quality frameworks to validate coverage, consistency, and accuracy of ESG datasets; document data lineage, metadata, and provenance to ensure auditability for enterprise clients.
- Data Taxonomy: Build and maintain a structured ESG data taxonomy that serves as the canonical reference across product and research teams.
- Research Output: Produce periodic research briefs on ESG data availability, vendor landscape changes, and emerging methodologies to inform product strategy and support client-facing teams with methodology documentation.
- Agile Participation: Contribute to sprint planning and backlog grooming, translating data research insights into clear, actionable requirements for engineering teams.
Qualifications
- Education: Bachelor's or Master's degree in Environmental Science, Sustainability, Data Science, Economics, Finance, or a related quantitative or social-science field.
- Domain Expertise: Demonstrated knowledge of ESG frameworks and standards (GRI, SASB, TCFD, CDP, ISSB/IFRS S1 & S2, UN SDGs) and the broader sustainability data ecosystem.
- Data Research Skills: Proven ability to identify, evaluate, and compare structured and unstructured data sources; strong proficiency with spreadsheets, data cataloging tools, and basic data manipulation.
- Analytical Rigor: A systematic approach to data quality assessment, source comparison, and evidence-based decision making.
- Communication: Strong written and verbal communication skills to convey complex data findings to both technical and non-technical stakeholders.
- AI & Agentic Architecture: (Strongly Preferred) Understanding of how LLMs, RAG pipelines, or AI agents consume and reason over structured datasets.
- Product Development: (Preferred) Experience contributing to product roadmaps, writing user stories, or working in sprint-based development cycles.
- Python / SQL: (Preferred) Ability to write scripts for data cleaning, validation, or exploratory analysis.
- Alternative Data Sources: (Preferred) Prior exposure to satellite imagery, NLP-derived datasets, corporate filings parsers, or ESG data vendor APIs (e.g., Refinitiv, MSCI, Sustainalytics, Bloomberg ESG).
