Data Science - Sustainability & ESG Data Research Analyst

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).