Career opportunities: Data Scientist Level 3

Introduction

Customer Insights and Analytics (CIA) is a data science team within the Cargo Digital Commercial Program. The team delivers data projects and generative AI use cases that support product innovation, including personalization, customer profiling, and service automation.

What are you going to do?

As a data scientist, you translate business challenges into actionable insights and develop AI proof of concepts. With an open and growth-oriented mindset, you take end-to-end responsibility: engaging with business stakeholders, gathering and preparing data, developing analytical content, maintaining and supporting the products you contribute to, and presenting insights that create new opportunities for products, features, sales, and services.

Where do you land?

You will join a challenging and dynamic environment that offers strong opportunities for career growth. A great diverse team and innovative working environment with international dynamics

By working closely with business users, you will be well positioned to build trust, deepen your domain knowledge, and deliver solutions that matter. At the same time, you will stay connected to the broader Air France KLM data science community, supporting your continuous learning and professional growth.

Your profile

We are looking for a passionate, experienced, and pragmatic data scientist: a curious builder who communicates effectively and thrives in a fast-paced environment. 

• You are an experienced data scientist, but you are driven more by creating measurable business value than by building the most sophisticated advanced solution


• You possess a bachelor's or master's degree in operations research, data science, or computer science.


• You are proficient in selecting appropriate machine learning techniques and are familiar with multiple ML methodologies, toolkits, and programming languages, such as Python.


• You can identify data pitfalls and biases, and you are comfortable moving between rapid prototyping and robust software engineering.


• You can quantify the business impact of data processes and prioritize critical issues effectively.


• You can explain complex modeling concepts clearly to both technical colleagues and non-technical stakeholders, and you are confident in advocating for your findings.


• Experience with ML industrialization practices is considered an advantage. You will work with IT who takes the lead in putting solution into production


• You stay up to date with the latest developments in machine learning and are committed to continuous professional growth.


• Fluency in English is required.


• Candidates with at least two years of hands-on professional experience in machine learning and data science will be considered.

Competencies