Datasets Consultant

At Mintel, we help businesses understand people, markets, and what comes next. As a global market intelligence agency, our understanding of consumers, innovation, and industry gives clients the clarity to act and the confidence to lead. With more than 50 years of expertise, we combine the real-world understanding of our experts with advanced technology to uncover patterns, anticipate change, and help organizations make smarter decisions.

We are looking for a Datasets Consultant to help us build, maintain, and continuously improve social datasets that support insight generation. The role combines analytical judgement, curiosity, market and category knowledge, taxonomy curation, and stakeholder collaboration.

You will independently manage assigned datasets, keep them relevant as categories and online consumer conversations evolve, and lead new dataset builds from initial scoping through to handover.

This is a Hybrid position based in Cape Town.

Key responsibilities:

Social dataset builds

• Lead dataset builds from scoping through to handover, balancing agreed requirements, quality standards and delivery timelines
• Define and maintain build plans, priorities, dependencies and risks
• Translate stakeholder needs into documented dataset requirements and acceptance criteria
• Apply appropriate techniques and proprietary tools, documenting key decisions and limitations
• Validate completed datasets against agreed requirements and provide documentation for ongoing use and maintenance

Social dataset maintenance

• Own the ongoing quality, relevance, and usability of assigned datasets
• Review dataset content and apply appropriate techniques to reduce irrelevant content and improve coverage of relevant conversations
• Monitor market developments, category changes, and emerging consumer conversations to identify gaps
• Update taxonomies and document material changes, decisions and known limitations

Process improvement

• Identify recurring challenges and implement practical improvements to datasets building and maintenance
• Contribute to team standards, guidance and consistent working practices
• Evaluate changes against their effect on quality, delivery efficiency, and usability
• Support the adoption of effective approaches through collaborative problem-solving and knowledge sharing

Stakeholder engagement

• Build effective stakeholder relationships and understand dataset needs, usage and priorities
• Communicate progress, decisions, risks, dependencies and limitations throughout builds and maintenance
• Use evidence and professional judgement to resolve competing requirements and manage expectations
• Agree priorities and acceptance criteria with relevant stakeholders

Cross-functional collaboration

• Represent social dataset expertise in cross-functional initiatives and contribute to shared decisions
• Test new tools and approaches, providing structured feedback grounded in dataset workflows and user needs
• Translate operational and stakeholder requirements into practical recommendations that support sustainable dataset delivery

Key outputs

• Completed datasets that meet agreed requirements and acceptance criteria
• Maintained datasets and taxonomies that reflect relevant market and consumer conversation changes
• Documented build plans, quality reviews, decisions, changes and handover guidance
• Clear stakeholder updates on progress, risks and limitations
• Evaluated process improvements and structured feedback on tools and approaches

Skills, competencies and experience

• Demonstrated experience building, maintaining or analyzing social datasets, with examples of independently delivered work
• Practical experience curating taxonomies and assessing the relevance and coverage of dataset content
• Analytical judgement to identify quality issues, investigate causes and implement improvements
• Ability to apply market and category knowledge to dataset scope and taxonomy decisions
• Experience managing delivery priorities, timelines, risks and dependencies
• Ability to translate stakeholder needs into documented requirements and communicate technical decisions clearly
• Evidence of contributing to process improvements and evaluating their impact
• Ability to collaborate across functions, share knowledge and provide constructive feedback
• Ability to learn and apply proprietary dataset tools and relevant analytical techniques

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