Data Ops Leader - Annotations & Datasets

Data Ops Leader – Annotations & Datasets

5+ years in data annotation, data operations, or related roles, with at least 2 years in a leadership position.
Experience working with annotation platforms (e.g., Labelbox, Scale AI, Supervisely)
Familiar with the operations of machine learning research teams and the role of annotated data in model training.
Experience building and managing internal annotation teams
Strong organizational and project management skills.
Experience working with cross-functional teams in a fast-paced, startup environment.

Stay on top of the landscape of vendors, including both capabilities and economics.
Drive strategic decisions about which annotation jobs to pursue with which vendor.
Quarterback discussions and negotiations with vendors in partnership with finance and leadership.
Ensure that our annotation investments align with Abridge’s research and product priorities, communicating frequently with builder leadership.
Work closely with scientists to produce clear specifications and identify appropriate datasets for each task.
Be the point person in charge of each annotation effort, ensuring that all efforts meet our product needs, comply with our obligations, and are completed swiftly.
Define and monitor quality metrics for annotation tasks.
Work with our AI science and engineering teams to curate the resulting datasets for model training and evaluation (storage, versioning, access controls, etc.).

Basic scripting or data manipulation skills (e.g., Python, Excel) are advantageous but not required.
Experience in medical or conversational data annotation.
Understanding of ETL/ELT processes, data governance, and security best practices.
Experience with data management tools and frameworks (e.g., SQL, BigQuery, DBT/Airflow).
Experience working with Cloud providers (AWS/GCP/Azure).
Experience with healthcare data and knowledge of HIPAA compliance.