Job Description

Quantitative Research Operations Manager

The Quantitative Research Operations Manager is a technical, behind-the-scenes role responsible for supporting the execution and quality of the organization's quantitative research.

You will work across studies to ensure surveys are programmed correctly, data is clean and accurate, and reporting outputs are client-ready. This includes program checking, data scanning and cleaning, data processing, report population, and rigorous numerical QC.

This is an ideal role for someone with solid Market Research experience who enjoys the technical and operational side of quantitative research, has exceptional attention to detail, and naturally notices when something in the data doesn't look right and can figure out why.

Duties and Responsibilities

Survey Programming & QA

• Review programmed surveys against questionnaires for accuracy and consistency
• Test survey logic, skips, piping, randomization, quotas, calculations, and respondent flow
• Conduct soft-launch data checks and identify potential programming or fieldwork issues
• Partner with researchers and programming vendors to troubleshoot and resolve issues

Data Quality & Processing

• Scan and clean respondent-level data throughout fieldwork and at study close
• Identify poor-quality respondents, inconsistent responses, suspicious open ends, speeders, straightliners, and other data-quality concerns
• Investigate unexpected data patterns and troubleshoot potential programming, sampling, or data-processing issues
• Support recodes, derived variables, banners, crosstabs, weighting, and significance testing
• Review data tables and other outputs for accuracy and consistency

Reporting & Analysis Support

• Populate PowerPoint reports with survey data, including charts and tables
• Check bases, percentages, significance, calculations, and data labels
• Conduct rigorous numerical QC of client deliverables
• Troubleshoot discrepancies across raw data, tables, and reporting outputs
• Prepare clean, analysis-ready data and outputs for research teams

Operational Excellence

• Serve as a centralized resource for quantitative research quality and technical execution
• Develop and improve standardized processes for program checking, data cleaning, reporting, and QC
• Identify opportunities to automate or streamline repetitive quantitative workflows
• Learn and leverage AI-powered tools and platforms to improve efficiency and quality

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