Internship Cargo Service Recovery Modeling

Introduction

Are you looking for a challenging internship within the logical supply chain? Do you want to make an impact in the international logistics of goods around the world for one of the main airlines in air cargo logistics?

In the logistical chain of air cargo, handling flows around the world—from fresh produce (flowers, fruits, vegetables) to pharma products, valuables, and e-commerce—service recovery is crucial for the customer when things don’t go as planned. We at AFKLMP Cargo are looking to revise our service recovery proposition to our customers after disruptions. We need better insights into what would be a reasonable proposition and the right trade-offs to be made.

What are you going to do?

We are looking for a bright student to study this feasibility and potentially use this as a graduation assignment. This will be an opportunity to apply your theoretical knowledge to practical problems in logistics and supply chain management.

Study the relation between the service recovery proposition and its feasibility.

Build a simulation model considering parameters such as:

• Product priority (e.g., perishable fruits vs general cargo)

• Customer priority

• Disruption reason and correlation

• Quality of service in execution

Model different parameters to gain insights into capacity constraints and time to market.

Where do you land?

 You will be based in the Pricing and Revenue Management (PRM) department of Air France KLM Martinair Cargo in Amsterdam, Schiphol Oost. The assignment covers service recovery out of our main hubs, Schiphol and Paris CDG airports. Within PRM we are responsible for the optimization of the Price and the Capacity of the cargo, including the service recovery. This includes all the cargo transported as well on our Full Freights are all our wide body bellies around the globe. Aside you will be supported by other Data Analysts team. 

Your profile

• You are in your last year of Econometrics/Mathematics or equivalent studies

• Proficiency in Python or R, SQL, and data analysis libraries (e.g. Pandas, NumPy); experience with data visualization.

• Knowledge of discrete event simulation, Monte Carlo methods, and optimization techniques is a plus

• You have affinity with logistical processes

• You are available for 6 months

• You have experience in modeling during your studies

• Curiosity about processes and eagerness to learn all about cargo service recovery

• You have critical eye

• You enjoy a multicultural environment

Competencies