At KLM Digital, we are looking for Data nerds who will help us to reach Predictive Maintenance on our test systems. We have plenty of digital products, complex airline systems and frequent go lives with new product features. How to use Data and AI best to keep our test systems up and running all the time, so we can deliver new features to our customers any time! In KLM Digital department, we have 40-50 products running to serve our passengers. Air France & KLM websites where our passengers buy their tickets, they check-in to select their seat or buy additional products like baggage, meal or upgraded seats, our ios or Android mobile apps to help passengers for their trips, social media bots where we interact with our agents and passengers. These applications are being developed and new innovative features are being added every day to our products.
Wat ga je doen?
We have multiple test systems to build the new innovation in these products simultaneously by multiple product teams. Test systems are crucial and must be up and running (despite of disturbances due to defects, wrong deployments, changing configurations and changing data) to keep the fast pace of development and support fast time to market. As part of our DevOps track, we would like to reach Predictive Maintenance in our test systems. So before an issue/defect happens which stops development and deployment, we predict and fix it beforehand. For this we need data! We are looking for a data scientist who can help us to take a snapshot of our current systems, analyze the data and define the patterns which occurs frequently on our test environment. We want our systems self-learning and self-maintaining! Are you up to this challenge?
We are looking for Data scientist interns to find out recurring failure patterns on our test systems, give us right insights and help us with reaching predictive maintenance so that we can go live any time with our new features for our passengers. If you have a Bachelor/Masters degree in Data science, you have proven analytical mindset and hands-on experience in applying statistical models don't miss out this opportunity!