Yanis Dahmani

Project — E-commerce Analysis

Tools: Python, Pandas, Matplotlib, Scikit-learn

→ Analysis of a dataset of 50,000 e-commerce transactions

→ RFM customer segmentation, identification of high LTV profiles

→ Churn prediction model (83% accuracy)

→ Deliverables: documented notebook + recommendation report

Training — Data Analyst · DataScientest (2024)

Recognized Certification ·

Python · SQL · Machine Learning · Data visualisation

For 10 years at Fraikin, I supported transport, courier, catering, and logistics clients in managing and optimizing their vehicle fleets.

My role was not limited to sales: I was in constant interaction with operations, workshops, and client management to address complex operational issues: vehicle availability, maintenance, resource shortages, meeting service levels, and cost control.

I worked on key issues such as asset management, anticipating maintenance operations, resolving non-payment situations, and supporting sales in targeting high-value, low-risk prospects.

This field experience allowed me to develop a global vision of transport operations: balancing performance, costs, and human constraints, a fine understanding of routes, energy constraints (fuel, tires, electrification), and the direct impact of operational decisions on profitability.