Remote | Human Data Manager - $40-$60/hour

Remote | Human Data Manager - $40-$60/hour Selected professionals will design, manage, and optimise human data operations, coordinate data collection and annotation workflows, establish performance metrics, and maintain high standards of data quality. The role combines operational project management with analytical problem-solving, cross-functional collaboration, and continuous process improvement to support the development of next-generation AI systems. Prior experience with AI training projects is not required. Key Responsibilities Human Data Operations & Workflow Management • 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 improvements to operational processes. • Develop repeatable procedures that support scalable data operations. • Maintain clear documentation of workflow requirements, operational processes, and project deliverables. Data Quality Assurance & Validation • Establish quality standards for annotation accuracy, data integrity, and validation procedures. • Monitor data workflows to identify inconsistencies, processing errors, and quality improvement opportunities. • Implement structured quality checks and review processes across assigned data operations. • Analyse quality trends and recommend improvements to data collection and annotation procedures. • Support consistent application of quality standards throughout the data production lifecycle. Performance Metrics & Operational Analytics • Define and monitor key performance indicators (KPIs) for operational efficiency, quality, and workflow performance. • Analyse datasets and operational metrics to identify trends and actionable insights. • Develop reporting frameworks that provide visibility into project performance and process improvements. • Evaluate operational results and translate findings into clear recommendations. • Support data-driven decision-making through accurate analysis and performance reporting. Cross-Functional Project Management & Collaboration • Coordinate with technical, operational, and business stakeholders to align data activities with project objectives. • Manage operational priorities, deliverables, and progress across assigned workstreams. • Communicate project updates, analytical findings, and improvement recommendations clearly. • Support collaboration between teams responsible for data collection, processing, quality, and analysis. • Take ownership of operational challenges and coordinate practical solutions. Process Optimisation & Scalable Operations • Evaluate existing processes to identify opportunities for greater efficiency and scalability. • Develop and refine workflows that support growing data volumes and changing project requirements. • Apply analytical reasoning to improve resource utilisation and operational performance. • Introduce practical improvements to reporting, quality monitoring, and workflow coordination. • Maintain a proactive, hands-on approach to operational execution and continuous improvement. Ideal Profile • Strong technical aptitude with 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 that support operational efficiency and scalability. • Familiarity with performance metrics, KPI reporting, and data-driven decision-making. • Strong analytical skills and the ability to interpret operational datasets. • Experience identifying workflow bottlenecks and recommending 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, particularly when explaining analytical findings. • Demonstrated 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 working environment. • Experience working independently and managing responsibilities in a remote setting. • Background in engineering, a technical discipline, or operations-focused project work is advantageous. • Experience with human data projects, annotation programmes, or related technical operations is preferred. • Familiarity with Excel, Tableau, Power BI, or comparable reporting and data visualisation tools is beneficial. • Knowledge of Python, SQL, or other relevant analytical tools is advantageous. • Internship or project-based experience in data management, AI/ML, or process optimisation is relevant. • Prior experience with AI model training or evaluation projects is not required. Engagement Details • Engagement Type: Full-time • Work Arrangement: Fully remote • Compensation: $40-$60/hour • 1 available opening • Regional Hiring: Recruitment is being conducted across multiple regions to support operational coverage, compliance, and time-zone alignment. Employment terms may vary by region. • Professional Focus: Human data operations, workflow management, operational analytics, and project coordination. • Technical Focus: Data annotation, data processing, quality validation, KPI reporting, and workflow optimisation. • Operational Focus: Scalable data collection, process improvement, performance monitoring, and cross-functional execution. • Responsibilities will include designing and managing human data workflows, monitoring operational performance, and maintaining data quality. • Assignments may involve annotation operations, dataset analysis, reporting development, and operational process improvement. • Deliverables will include workflow documentation, operational reports, quality assessments, and actionable improvement recommendations. • Experience with Excel, Tableau, Power BI, Python, or SQL is advantageous. • Candidates with engineering backgrounds, technical project experience, or exposure to human data operations are particularly relevant. • Strong independent execution, analytical judgement, and stakeholder communication are important for successful performance. • Previous experience with AI training projects is not required.