Human Data Operations Strategist
Manages and optimizes client data annotation workflows for AI models, ensuring high-quality data through process design, auditing, and cross-functional collaboration. Requires 3-7 years experience, Python/SQL proficiency, and strong project management in AI operations.
About the job
Responsibilities
- Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams
- Ensure the highest standards of data quality by designing and refining annotation processes, auditing results, and implementing feedback loops
- Act as a trusted advisor to clients, helping them design and implement the best data annotation workflow for their human annotation process
- Provide guidance and feedback to the annotation team, ensuring team members are equipped with the context and skills needed to perform high-quality work aligned with project requirements and best practices
- Work closely with product and engineering teams to drive improvements in AI training data processes, tools, and methodologies
Requirements
- 3–7 years of professional experience, with a strong preference for backgrounds in top-tier strategy consulting and/or operations or data roles at leading AI or technology companies
- Proven ability to own complex, multi-stakeholder workflows end-to-end — from scoping and planning through execution, quality assurance, and iteration
- Working proficiency in Python or SQL, with the ability to query data, automate workflows, or audit annotation outputs; broader familiarity with relational databases or data annotation tooling equally valued
- Experience designing or optimising data operations processes with a strong eye for quality, consistency, and scalability — ideally in a context involving human-in-the-loop workflows or structured labelling tasks
- Demonstrated ability to engage effectively with both technical stakeholders (ML engineers, data scientists) and non-technical clients, translating requirements clearly in both directions
Nice-to-haves
- Hands-on experience with computer vision, generative AI, or multimodal data workflows
- Prior exposure to data annotation platforms or quality management frameworks
- Experience coaching or managing operational teams
Skills
Python, SQL, Data Annotation, AI Workflows, Machine Learning, Data Quality, Relational Databases, Computer Vision, Generative AI, Annotation Platforms
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