Human Data Operations Strategist

About the Role

As a Human Data Operations Strategist, you will play a critical role in managing and optimising data annotation and machine learning workflows for our clients. You will work closely with cross-functional teams, including clients, annotation specialists, and machine learning engineers, to ensure high-quality data is available for AI models.

What You'll Do

• 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

Who We're Looking For

• A sharp, execution-oriented operator with a consulting or AI company pedigree — you bring structured thinking, strong project management instincts, and a bias for getting things done
• Analytically rigorous and comfortable with ambiguity — you break down complex operational challenges from first principles and build clear, actionable plans to solve them
• Technically fluent enough to get hands-on with data — whether that's querying a database, auditing annotation outputs, or automating a workflow in Python
• Passionate about AI and machine learning, with genuine curiosity about how data quality and operations underpin model performance
• A natural communicator who can translate fluidly between ML engineers and non-technical clients, keeping complex multi-stakeholder projects on track
• Entrepreneurial and collaborative — you thrive in fast-paced environments and take ownership without waiting to be told what to do

Experience 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
• Bonus: 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

Benefits

• Competitive salary, commission, and meaningful equity in a high-growth start-up
• Clear, accelerated growth opportunities as the company scales rapidly
• Strong in-person culture: 4 days/week
• Flexible PTO to fully recharge
• Annual learning & development budget
• Comprehensive health, dental, and vision coverage
• Frequent travel opportunities across the U.S., London, and Europe
• Bi-annual company offsites, twice-weekly team lunches, and monthly socials