Top Tech Jobs & Startup Jobs in Boston, MA

Own sales enablement across Prolific’s AI and research businesses. Build onboarding, training, launch-readiness programs, sales toolkits, competitive intelligence, win-loss analysis, customer proof, and buyer interview programs. Use CRM and call data to identify deal insights, improve messaging, support product feedback, and measure win rates, deal velocity, rep ramp time, and content usage. Partner closely with sales, product, customer success, and RevOps to improve seller effectiveness and revenue outcomes.

Lead Prolific’s participant growth strategy across acquisition, activation, engagement, and retention. Build scalable acquisition channels, partnerships, and growth operations while managing a multidisciplinary team spanning marketing, recruitment, partnerships, and community. Use funnel metrics, cohort analysis, CAC, LTV, and marketplace data to drive decisions. Partner with Product, Engineering, Data Science, and Operations to improve participant journeys, automate processes, and deliver sustainable marketplace growth.

Manage the operational delivery of human data for a strategic AI customer. Responsibilities include translating requirements into workflows, managing participant pools and onboarding, tracking supply and quality, leading cross-functional projects, resolving operational issues, documenting processes, and improving scalability with Product and Engineering. The role also supports participant assessment and certification programs while serving as an operational point of contact for delivery teams.

Leads complex AI client projects from requirements gathering through delivery, serving as the primary client contact and coordinating Sales, Operations, Product, and Engineering. Responsibilities include defining scopes and delivery plans, managing risks, quality, timelines, budgets, profitability, and KPIs, resolving execution challenges, and improving scalable processes for AI project delivery.

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 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.