Remote | Human Data Manager — $40–$60/hour
About The Position
The Human Data Manager designs, manages, and optimises human data operations supporting AI training and evaluation initiatives. The role combines operational project management, analytical problem-solving, cross-functional collaboration, and process improvement. Responsibilities include coordinating data collection and annotation workflows, establishing performance metrics, monitoring quality, and improving processes to support efficient, scalable data production. Prior experience with AI training projects is not required. The position is fully remote and full-time, with compensation of $40–$60 per hour. Recruitment is conducted across multiple regions to support operational coverage, compliance, and time-zone alignment; employment terms may vary by region. Work may include annotation operations, dataset analysis, reporting development, and operational process improvement. Deliverables include workflow documentation, operational reports, quality assessments, and actionable improvement recommendations. There is one available opening.
Requirements
- Strong technical aptitude and practical experience in data operations, data analysis, annotation, or workflow optimisation.
- Understanding of structured data collection, processing, validation, and quality assurance.
- Experience coordinating projects, operational activities, or technical workflows.
- Ability to design and improve processes for operational efficiency and scalability.
- Familiarity with performance metrics, KPI reporting, and data-driven decision-making.
- Strong analytical skills and ability to interpret operational datasets.
- Ability to identify workflow bottlenecks and recommend practical improvements.
- Understanding of data integrity, annotation quality, and validation principles.
- Excellent organisational skills and attention to detail.
- Ability to manage multiple priorities and take ownership of operational deliverables.
- Strong written and verbal communication skills, including explaining analytical findings.
- Ability to collaborate effectively with technical and non-technical stakeholders.
- Resourceful, proactive approach to problem-solving and operational execution.
- Adaptability and willingness to learn in a fast-paced environment.
- Ability to work independently and manage responsibilities in a remote setting.
Nice To Haves
- Background in engineering, a technical discipline, or operations-focused project work.
- Experience with human data projects, annotation programmes, or related technical operations.
- Familiarity with Excel, Tableau, Power BI, or comparable reporting and data visualisation tools.
- Knowledge of Python, SQL, or other relevant analytical tools.
- Internship or project-based experience in data management, AI/ML, or process optimisation.
- Experience with AI model training or evaluation projects is not required.
Responsibilities
- Design and manage structured workflows for data collection, annotation, processing, and analysis.
- Coordinate operational activities to support consistent and efficient human data production.
- Identify workflow bottlenecks and implement practical process improvements.
- Develop repeatable procedures and maintain documentation of workflow requirements, processes, and project deliverables.
- Establish quality standards for annotation accuracy, data integrity, and validation procedures.
- Monitor workflows for inconsistencies, processing errors, and quality improvement opportunities; implement quality checks and review processes.
- Analyse quality trends and recommend improvements to data collection and annotation procedures.
- Define and monitor KPIs for operational efficiency, quality, and workflow performance.
- Analyse datasets and operational metrics, develop reporting frameworks, and provide clear recommendations based on findings.
- Coordinate with technical, operational, and business stakeholders to align data activities with project objectives.
- Manage priorities, deliverables, and progress across assigned workstreams; communicate project updates and analytical findings.
- Coordinate collaboration across teams responsible for data collection, processing, quality, and analysis.
- Evaluate processes and develop scalable workflows for growing data volumes and changing project requirements.
- Improve resource utilisation, reporting, quality monitoring, and workflow coordination.
- Take ownership of operational challenges and coordinate practical solutions while maintaining a hands-on approach to execution and continuous improvement.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
