About the job

In this role you will bring innovative algorithms to life and shape business processes like capacity planning through advanced machine learning and optimization techniques. You will design, develop, and maintain cutting-edge models that directly impact millions of customers and drive our business success. Ready to innovate and make an impact? Apply now and join Team Orange in Pullach, close to Munich.

YOUR ROLE AT SIXT

• You make data science solutions production-ready, monitored, robust and scalable
• You ensure a reliable and scalable deployment foundation for workforce management optimization algorithms and ML models following MLOps guidelines
• You design, develop and maintain machine learning models and optimization algorithms focused on demand forecasting, shift planning and staffing optimization
• You collaborate effectively across departments, partnering closely with Workforce Management teams to transform operational challenges into data-driven solutions
• You establish and extend tools to automate the Data Science Tech Stack and continuously enhance MLOps processes including model deployment and data pipelines
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YOUR SKILLS MATTER

• Experience You have deep experience building and operating machine learning models and optimization algorithms in production with strong proficiency in Python and cloud infrastructure (preferably AWS)
• Data Engineering You possess strong knowledge of data modelling, database systems and ETL processes
• AI-Assisted Development You use AI-assisted tools thoughtfully and know how to apply them in ways that remain reviewable, reliable, and useful in day-to-day engineering work
• Monitoring & Logging You have deep expertise in monitoring and logging tools to detect and resolve issues proactively in ML models and supporting infrastructure
• Workforce Management Domain You are familiar with workforce management concepts like forecasting, capacity planning or scheduling – a strong plus
• Communication & Collaboration You demonstrate strong communication skills in English