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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