Extract Skills and Roles from Job Postings for a Recruiter Tool
Overview
What this challenge is about.
You will fine-tune a token classifier on 30,000 job postings to extract skills and roles, then normalize them to ESCO URIs. You get a verifiable certificate.
The scenario
The edtech (~45 staff) operates across Spain, Portugal, and Italy and uses career-path insights as a differentiator with university partners.
The Brief
What you'll do, and what you'll demonstrate.
Turn raw job-posting text into ESCO-normalized (role, skill, seniority) tuples with measurable end-to-end accuracy.
Earning criteria — what you'll demonstrate
- Fine-tune a token classifier on a real IE task
- Normalise extracted entities to a public taxonomy (ESCO)
- Evaluate end-to-end IE + normalization accuracy
- Design a refresh strategy for taxonomy-dependent pipelines
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Information Extraction
Apply information extraction to solve real industry problems and demonstrate production-level capability.
- Token Classification
Apply token classification to solve real industry problems and demonstrate production-level capability.
- Esco Taxonomy
Apply esco taxonomy to solve real industry problems and demonstrate production-level capability.
- Entity Normalization
Apply entity normalization to solve real industry problems and demonstrate production-level capability.
- Fine Tuning
Apply fine tuning to solve real industry problems and demonstrate production-level capability.
- Evaluation
Apply evaluation to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
NLP Engineer
Fine-tuning a token classifier plus a normalization layer is the day-to-day of NLP engineers at HR-tech and edtech vendors.
This challenge sharpens
- information-extraction
- token-classification
- entity-normalization
Machine Learning Engineer
End-to-end accuracy reporting plus a refresh strategy is core MLE work for taxonomy-dependent pipelines.
This challenge sharpens
- fine-tuning
- evaluation
- entity-normalization
Data Engineer
Owning the ESCO mapping refresh strategy and the pipeline that consumes it is the data-engineering backbone of any career-path product.
This challenge sharpens
- esco-taxonomy
- entity-normalization
- evaluation