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Car Sharing meets Data Science

The usage of Artificial Intelligence greatly benefits modern companies in optimizing and automatizing the processes. Scalable machine learning algorithms generate knowledge from data, support decision makers and give business a competitive advantage.

Ecodia contributed to the development of multiple end-to-end Data Science solutions to bring forward Sixt’s automated price optimization initiative.

Together with our client’s team we accomplished the process of gathering requirements from stakeholders, specifying problem definition, identifying predictive capacity in the raw data, engineering additional predictive features, experimenting with various model types, and deploying on cloud. The result is a highly flexible and configurable codebase enabling choosing from various state-of-the-art models and optimization techniques. We supported our client with maintenance of the product and extending it with new use cases.

Machine Learning Pipeline Development

• Development of a flexible Python machine learning stack for regression and classification tasks (Scikit-Learn, Tensorflow, Statsmodels)
• Monitoring for data drift detection and model accuracy evaluation

Cloud Machine Learning Operations

• Implementation of a CI/CD workflow for automatic training and provision multiple machine learning models
• Deployment Automation for AWS with Terraform

Sixt SE

Sixt SE is a global car rental and mobility service provider with strong presence in Europe and US. It offers a diverse fleet of vehicles, online reservations, and innovative mobility solutions in over 100 countries worldwide.

Sixt is one of the largest car rental companies in the world with regards to assets, revenue and fleet size.

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