Research Operations Manager - Data Quality

Research Operations Manager – Data QualityPrimarily responsible for the escalation of data quality issues generated by ongoing and dynamic research operations. Our client is dedicated to ensuring the highest quality of research findings – accurate, representative of the target groups, and with the highest levels of trustworthiness. The ideal candidate will have a unique combination of analytical experiences, research expertise, and operational savviness that will enable them to active manage root causes, recommend corrective action, and strengthen the feedback loop between customers, internal teams, and partner panels.Moreover, this person would thrive in a variety of tasks regarding quantitative research, sampling science, and client communications. Key ResponsibilitiesDefine and Evolve the Data Quality Escalation Protocol● Design a repeatable, transparent investigation framework that ensures consistency, accountability, and learning across teams. ● Establish processes and communication templates to improve response speed and clarity when data quality concerns arise. ● Maintain a centralized log of issues and resolutions to track trends and proactively inform product or panel improvements.Active Management of Data Quality Across All Research Event●The primary POC for all project-level data quality escalations, leading cross-functional investigations to determine scope, cause, and resolution path. ● Survey Design. Evaluate survey design, targeting, sampling strategy, and respondent behavior patterns● Identify Root Causes of Data Quality Issues, based on a thorough understanding of survey design, sample source, platform logic, and respondent engagement patterns. Internal Collaboration and Prevention● Deliver feedback loops to Product, Panel Partnerships, and Customer Experience teams, turning case learnings into systemic improvements.○ Example: identify recurring low-quality sources from a specific panel partner and collaborate with Panel Partnerships to requalify or suspend usage. ○ Example: flag recurring design-driven quality issues to Research Services or Customer Success to recommend Design Navigation support for affected customers. Customer-Facing Resolution & Communication● Support the development of quality dashboards and trend analyses to quantify the impact of interventions and identify emerging risks. ● Produce data quality-related content, such as training sessions and blog posts, that communicates (1) CLIENT’s philosophy and processes related to data quality, as well as (2) preventive actions customers can take to proactively ensure data quality.● Partner with Customer Success Managers and other customer experience team members to communicate findings, impact, and corrective actions to customers. Ability and confidence to lead with executive-ready messaging, both internally and with customers. ● Translate technical and methodological explanations into clear, customer-friendly narratives that preserve confidence and trust. ● Provide actionable recommendations to customers — such as adjustments to future survey designs, targeting settings, or fielding expectations — to prevent recurrence Apply tot his job