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Prolific seeks Study Participants for academic and applied research. Participants will complete studies such as surveys and feedback tasks. Compensation is up to $18 per hour. Requirements include attention to detail and a reliable internet connection.

As a Study Participant, you will complete academic research studies, answer surveys, and provide feedback to contribute to high-quality research outcomes, with competitive pay rates and flexible hours.

As a Study Participant, you will complete various paid research studies, provide feedback, and contribute to high-quality research outcomes.

The Participant Recruitment Partner will identify and engage top-tier participants, manage client-specific recruitment operations, and enhance the participant pool quality through data-driven insights and collaboration.

As a Study Participant, you will take part in research studies, complete surveys, provide feedback, and contribute to research outcomes. Must have attention to detail and the ability to work from home with a reliable internet connection.

As a Study Participant, you will engage in various research studies, completing tasks like surveys and experiments while providing feedback. Strong attention to detail and a reliable internet connection are necessary.

The Partner Growth Manager will build executive partnerships, drive revenue growth across the partner ecosystem, and represent Prolific at industry events, focusing on relationships in the US research and SaaS sectors.

Lead scoping, design, and delivery of complex human-data projects for AI clients. Own study design, protocols, rater onboarding and QA, pilot execution, and cross-functional coordination to scale repeatable workflows and document playbooks to improve operational readiness and automation.

Design and own end-to-end data quality systems for managed AI data studies: define rubrics, sampling plans, automated checks, launch gates, drift detection, dashboards, and calibration. Investigate integrity issues, run root-cause analysis, build automation in Python/SQL, and partner with Product, Engineering, and Operations to embed quality controls, train reviewers, and scale repeatable quality playbooks across programs.

The role involves training and evaluating AI models using real accounting expertise, focusing on financial reporting and management accounting tasks.