Datasets Consultant
mintel
- Cape Town, South Africa
- Mid Level
- Posted
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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