Responsibilities

• Design and develop pricing models based on mathematical algorithms, predictive models (forecasting, regression, time series, ML), and optimization techniques (price optimization, revenue/yield management).
• Translate business challenges into data science use cases and deliver actionable pricing recommendations.
• Build and validate proofs of concept (Po C) to demonstrate the value of new approaches before industrialization.
• Work with large datasets using Python and Spark, ensuring scalability and performance.
• Design, schedule, and monitor data and model pipelines using tools such as Airflow, ensuring reliability and traceability.
• Contribute to the implementation of CI/CD pipelines, ideally with Jenkins, to automate testing, deployment, and monitoring of models.
• Deploy and operate solutions in the cloud, preferably AWS (experience with Azure or GCP is also valued).
• Collaborate with business ...