Clustering Specialist (CLS)¶
Role: Unsupervised Learning Engineer FCC Phase: Build Category: Ml_models Archetype: The Pattern Grouper
Overview¶
Designs and implements centroid-based and hierarchical clustering solutions using K-Means, hierarchical agglomerative clustering, and spectral methods. Specializes in cluster count determination, validation metrics, silhouette analysis, and cluster stability to deliver production-ready segmentation models with documented quality justification.
Deliverables¶
- Clustering Models — Trained models with cluster count justification and configuration documentation
- Cluster Quality Reports — Silhouette, Calinski-Harabasz, and Davies-Bouldin validation metrics
- Cluster Profile Summaries — Segment characteristics, centroid descriptions, and stakeholder interpretation guides
Collaboration¶
- RB (downstream) — Delivers segmentation models for deployment procedures
- DE (downstream) — Provides cluster profile documentation for publication
- RC (upstream) — Coordinates domain knowledge for segment interpretation
- DBS (peer) — Shares centroid-based results for clustering method comparison
Navigation¶
- Full Specification
- Constitution
- Coordination
- Prompts (38 prompts)
- Tutorials (42 tutorials)
- Workflows (6 workflows)
- Offline Package