Data Analyst – Ground Truth Annotation

About the role

Moody's is looking for a Data Analyst to own the end‑to‑end lifecycle of ground‑truth data collection campaigns. You will translate machine‑learning needs into high‑quality labeled datasets that power core computer‑vision products, working closely with ML and Data Science teams.

Key responsibilities

• Partner with ML and Data Science leads to define label taxonomies and concrete labeling tasks.
• Design and run internal gold‑standard campaigns to validate taxonomies and cover edge cases.
• Configure and manage annotation projects, including uploading imagery, geometries, and metadata.
• Coordinate with external labeling vendors, providing taxonomy training and ongoing feedback.
• Evaluate vendor performance using gold datasets, confusion matrices, and quality reports.
• Launch and monitor production labeling campaigns, tracking throughput, SLAs, and overall quality.

Required profile

• Experience running or supporting data labeling and annotation efforts, including campaign management, QA, or vendor coordination.
• Hands‑on familiarity with professional labeling platforms such as Labelbox, Dataloop, Scale, or similar tools.
• Strong analytical mindset with ability to interpret label distributions, consensus metrics, and error patterns.
• Master's degree in a quantitative, analytical, or technical field.

Required skills

• Python for analysis and automation (including Jupyter notebooks).
• SQL for data extraction and basic analysis.
• Spreadsheets (Excel) for data manipulation.
• Labeling platforms: Labelbox, Dataloop, Scale.

What we offer

• Opportunity to work on cutting‑edge AI and risk‑assessment projects.
• Collaborative, inclusive environment that values diverse perspectives.