Encord
Operations
HumanDataOperationsStrategist
“Human Data Operations Strategist at Encord. Skills: process management, cross-functional coordination, vendor/stakeholder management, operational metrics, resource planning, continuous improvement, data annotation, machine learning workflows, AI models, data quality, client advisory, AI training data processes. managing and optimising data annotation and machine learning workflows for clients. Oversee data annotation projects, translating complex AI and machine learning requirements into clear w”
What You'll Achieve.
ensure high-quality data is available for AI models; ensure team members are equipped with the context and skills needed to perform high-quality work aligned with project requirements and best practices
Industry & Context.
break down complex operational challenges from first principles and build clear, actionable plans to solve them
Travel for customer visits, events, and conferences across the UK and Europe
What They're Looking For.
Must Have
3–7 years of professional experience, 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, Experience designing or optimising data operations processes with a 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 Have
backgrounds in top-tier strategy consulting and/or operations or data roles at leading AI or technology companies, broader familiarity with relational databases or data annotation tooling equally valued, hands-on experience with computer vision, generative AI, or multimodal data, prior exposure to data annotation platforms or quality management experience, coaching or managing operational teams
What You'll Do.
managing and optimising data annotation and machine learning workflows for clients
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
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
How You'll Work.
Team & Collaboration
work closely with cross-functional teams, including clients, annotation specialists, and machine learning engineers; engage effectively with both technical stakeholders (ML engineers, data scientists) and non-technical clients; collaborative
Communication Scope
natural communicator; translate fluidly between ML engineers and non-technical clients; translating requirements clearly in both directions
Process & Methodology
project management instincts, own complex, multi-stakeholder workflows end-to-end — from scoping and planning through execution, quality assurance, and iteration, keeping complex multi-stakeholder projects on track
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