Phoenix - Your AI AssistantResearcher / Data Analyst – Future Skills Taxonomy Development
- Posted:
- Proposals: 16
- Remote
- #4445088
- Expired
Peyrat-le-Chateau 
Description
Experience Level: Entry
We’re looking for a skilled researcher or data analyst to develop a Future Skills & Competency Taxonomy for learning, workforce analytics, and AI-based assessments. The project involves compiling a structured dataset of 1,000–2,000 skills, sub-skills, and emerging roles aligned with Industry 4.0–5.0 trends.
Scope:
Research global frameworks (WEF, ESCO, O*NET, Lightcast, SkillsFuture, etc.)
Identify future-critical skills across key sectors (tech, services, manufacturing, green economy)
Build a multi-level taxonomy (Domain → Category → Skill → Sub-skill → Behaviour)
Tag skills (technical, cognitive, digital, sustainability) and define proficiency levels
Deliver structured Excel/CSV dataset with job role links and trend insights
Validate using job market data (LinkedIn, Lightcast, etc.), with Malaysia/Asia focus
Requirements:
Experience in skills frameworks, HR analytics, or competency modelling. Strong research and data organisation skills.
Duration: 2–4 weeks (flexible)
Budget: Open / Fixed price preferred
Scope:
Research global frameworks (WEF, ESCO, O*NET, Lightcast, SkillsFuture, etc.)
Identify future-critical skills across key sectors (tech, services, manufacturing, green economy)
Build a multi-level taxonomy (Domain → Category → Skill → Sub-skill → Behaviour)
Tag skills (technical, cognitive, digital, sustainability) and define proficiency levels
Deliver structured Excel/CSV dataset with job role links and trend insights
Validate using job market data (LinkedIn, Lightcast, etc.), with Malaysia/Asia focus
Requirements:
Experience in skills frameworks, HR analytics, or competency modelling. Strong research and data organisation skills.
Duration: 2–4 weeks (flexible)
Budget: Open / Fixed price preferred
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Do you already have a preferred skills framework as the primary reference (e.g., ESCO, ONET, WEF), or should the taxonomy be built by merging multiple frameworks from scratch?