As a Data Processing Specialist, you are responsible for end-to-end data processing across market research projects, including data manipulation, data wrangling, coding, validation, and simple and complex tabulation. The ultimate deliverable of this team is accurate, analysis-ready data tables that meet agreed specifications and quality standards.
You support research delivery from the data processing point of view: reviewing questionnaire and database setup, restructuring and merging datasets, generating and applying coding frameworks, running simple and complex tabs, executing quality checks, using Human8 tools such as visual tagging and text highlight where relevant, and ensuring outputs are clean, consistent, traceable and ready for downstream analysis by the appropriate specialist pillars.
The role is expected to be confident in core data processing tools, including SPSS, WinCross, Q, Data Wizard, Copilot and relevant Human8 proprietary tools, while acting as a technical sparring partner for Project Services, Client Service Teams and senior experts on data processing quality, feasibility and tabulation requirements.
Data Quality Assurance
- Critically assess the technical side of questionnaires, including filters, routing, piping, quota logic and database structure, to ensure analysis-readiness.
- Recommend implementation changes during or after project setup where the data structure, routing logic, coding requirements or tabulation specifications create quality risks.
- Execute and guide robust data quality checks, including consistency checks, missing-data checks, validation against questionnaire logic and output accuracy checks.
- Act as a knowledgeable sparring partner for project teams on technical data questions, quality risks and analytical feasibility.
Data Handling, Processing & Automation
- Prepare datasets for tabulation through data manipulation, data wrangling, restructuring, merging, code frame creation, recoding, weighting support, complex computations and other data management activities.
- Independently process standard and moderately complex datasets using approved tools and documented methods.
- Produce accurate simple and complex tabs, including crosstabs, banners, breaks, filters, derived variables and other standard or project-specific tabulation requirements.
- Use relevant Human8 tools and methods, including visual tagging and text highlight, to support coding, classification, quality review and insight preparation where applicable.
- Automate recurring processing tasks where feasible by applying known techniques, reusable syntax, templates, macros, Copilot-assisted workflows or other approved efficiency improvements.
- Maintain clear processing documentation so that outputs are traceable, repeatable and easy to review.
- Partner with senior experts on complex data structures, advanced transformations, non-standard tabulation or technically challenging project requirements.
Method Management, Guidance & Continuous Improvement
- Evaluate standard data processing and tabulation steps, identifying opportunities to improve quality, efficiency, automation and consistency.
- Create or improve technical manuals, step-by-step guides, checklists and reusable templates for standard and recurring project types.
- Provide technical guidance to colleagues on tools, output checks, data issues and troubleshooting.
- Stay current with commonly used data processing and tabulation tools, including SPSS, Q, WinCross, Data Wizard, Copilot and relevant Human8 proprietary tools.
- Contribute to knowledge sharing and capability building across the Data Processing community.
Tools & Platforms
- Use core data processing platforms such as SPSS, WinCross, Q and Data Wizard to prepare, manipulate, tabulate and validate research data.
- Use Copilot and other approved productivity tools responsibly to support efficiency, documentation, checking and workflow improvement.
- Use Human8 tools and methodologies, including visual tagging and text highlight, to support coding, classification, quality review and synthesis of qualitative or open-ended data where relevant.
Success Measures / KPIs
- Accuracy and completeness of processed datasets, manipulated data files, coded outputs, simple tabs and complex data tables
- Timeliness of data processing deliverables against agreed project milestones
- Quality of technical questionnaire/database reviews and early identification of analysis and tabulation risks
- Effectiveness of data quality checks and reduction of rework or output corrections
- Effective use of required tools, including SPSS, WinCross, Q, Data Wizard, Copilot, Human8 visual tagging and text highlight
- Contribution to automation, documentation, reusable methods, technical guidance and continuous process improvement
Education and experience
- Relevant Bachelor’s degree in Data, Statistics, Computer Science, Business Analytics etc
- Minimum 1-2 years of experience.
- Manage English at a professional level (verbal/ writing) and able to have a fluent and accurate conversation.