Data Scientist IFS

At KLM, you contribute to unforgettable journeys — no matter what your role is.

You develop new, in-depth data-driven insights and (predictive) models that help manage the cabin crew planning chain — ensuring that KLM remains one of the world’s leading players in crew scheduling.

Our 9,500+ cabin crew members are not only deployed efficiently, but can also bring out the best in themselves on every single flight!

What will you do?

Everything falls into place with you at the helm as Data Scientist within the Planning & Assignment department of Inflight Services (P&A). You will operate at the intersection of crew scheduling, information technology, big data, and workforce planning. With your fresh perspective and expertise, you create new data-driven insights and (predictive) models that improve our scheduling and capacity management processes. You know exactly how to use models and techniques to extract meaningful information from large volumes of data — leading to better decisions. The enormous amount of data generated daily by our 9,500 crew members, KLM flights, and scheduling systems doesn’t intimidate you — you see it as an exciting challenge.

You’ll work as part of multidisciplinary teams with business experts, end users, and data and software engineers. Together, you’ll turn models into practical business products that are actually used within the organization.

In addition, you will:

• Proactively engage with the business to understand their challenges and needs;
• Regularly connect with other data scientists in the KLM data community to share knowledge and learn from one another;
• Act as a data (science) advisor and consultant for your colleagues.

This role allows you to use your innovative ideas to optimize the strategic workforce planning of cabin crew and ensure that rosters align even better with employees’ preferences.

Where do you land?

You’ll be based at Schiphol-Oost within the Planning & Assignment (P&A) department of Inflight Services, alongside around 60 enthusiastic colleagues who know their craft and work together daily to deliver results. Together with Chain & Business Consultants, Project Managers, and a Data Analyst, you will form the P&A Development team — the innovative core of the department. You will report directly to the Manager P&A Development.

Your profile

You are an experienced, enthusiastic, and results-oriented data scientist. You’re entrepreneurial, unafraid to experiment, and known for your creative problem-solving skills. You have strong analytical capabilities — quickly getting to the heart of complex issues — and the communication skills to explain your work clearly, even to non-technical colleagues. Perfect!

In your toolkit:

• A Master’s degree in a quantitative field such as Econometrics, Mathematics, or Data Science;
• 2–5 years of experience as a Data Scientist in innovative projects;
• Strong programming skills, preferably in Python;
• Knowledge of data extraction using SQL;
• Solid experience with Machine Learning (a must).

Explore the perks of working with us

• If your position allows this: working from home and working from abroad for up to 8 weeks (EU and Caribbean)
• 2% development budget to be spent freely
• Plenty of room for personal development and great career opportunities
• Substantial discount on airline tickets (if you have been employed for at least 6 months)

What do we offer

• A challenging role at an unique employer in the Netherlands;
• A gross salary between €4,252.77 and €6,075.38 per month;
• Plenty of room for personal development and wonderful career opportunities;
• A good pension scheme and 8% holiday pay;
• An end of the year bonus of 8,33%;
• 25 days of paid holiday and 5 extra days off;
• Great discounts on airline tickets (if you have been in service for at least 6 months);
• A sustainable transport policy, which allows you, among other things, to use all public transport for your commute within the Netherlands, free of charge;
• Discount of your health insurance;
• A personal budget for sustainable employability.