PYPYLAB

Enterprise & Commercial Cases

Engineering for business outcomes.

Real business problems, data modeling and decision support. Protected cases expose only desensitized summaries; full details are reserved for interview discussion.

C01 · VITASOY

Channel-stuffing investigation → discount mechanism optimization

From order-level anomaly and value-leakage analysis to discount-mechanism audit review and control optimization.

PythonData EngineeringAnomaly DetectionAudit AnalyticsSales AnalyticsBusiness Rules
Business questionHow can transaction-level anomalies expose systematic value leakage and support control redesign?
🔒 Protected case · interview access
C02 · VITASOY

Cabinet lifecycle → procurement decisions

Quantitative asset-lifecycle analysis using desensitized enterprise data to support retain, replace and procurement decisions.

Lifecycle AnalyticsData ModelingProcurement AnalyticsDecision Support
Business questionWhich assets should be retained, replaced or newly purchased, and on what evidence?
🔒 Protected case · interview access
C03 · YUNFANG DATA

Data governance → pricing model

A stable data and pricing foundation built around commercial real-estate governance, data structures and algorithmic models.

PythonData GovernanceETLData ModelingPricing Model
Engineering questionHow should heterogeneous commercial data be structured, governed and transformed into stable pricing features?
C04 · COMMERCIAL MODELING

Site selection → commercial scenario profiling

A computable and explainable site-selection model built from POI, spatial context and commercial scenario features, then delivered through Site Scout.

Spatial AnalyticsFeature EngineeringPOI ModelingCommercial ModelingMCP
Modeling questionHow can local commercial context be represented as features that support a practical site-selection decision?