Human Data Manager

$40–60/hr

rate as listed

Workload: ~15h/week
Engagement: Project-based
Location: Worldwide
Field: Generalist

Manage human data workflows for annotation, collection, processing, analysis, and quality validation. This remote, full-time role focuses on operational metrics, scalable processes, and clear recommendations for teams training AI systems.

The work

You will design and manage workflows that move human-generated data through annotation, collection, processing, validation, and analysis. Day-to-day work includes monitoring KPIs, investigating workflow performance, maintaining reporting frameworks, identifying data-quality issues, and recommending process changes that improve accuracy, efficiency, and scale.

What the platform screens for

The screening is likely to focus on concrete examples of data analysis, annotation operations, or workflow optimization. Expect follow-up questions about how you selected KPIs, validated data, found the cause of an operational problem, and translated findings into action. An engineering or technical background and experience with human data projects are preferred. Excel, Tableau, and Power BI are preferred visualization tools, while Python and SQL are preferred programming languages. Prior AI experience is not required.

Logistics

The role is remote and full-time. Hiring is taking place across multiple regions for coverage, compliance, and time-zone alignment, so the expected working schedule and employment terms may depend on region. The listing does not describe the work as asynchronous.

Pay band: $40–60/hr

What they look for

Project Management
Data Operations
Quality Analysis
Human Data

Included with this listing

Interview prep — 10 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: This tests whether your relevant experience is specific and verifiable, including the workflow, your personal ownership, the data involved, and the result.
A strong answer: Choose one project and state the starting problem, data volume or operating context, your exact responsibilities, the actions you took, and a measurable outcome. Separate your work from the broader team's contribution.
Where people lose it: Candidates lose points by describing a team initiative without clarifying what they personally built, analyzed, or changed.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.