Beschreibung
• Developing solutions together with a multi-disciplinary team of subject domain experts, project managers, engineers, data scientists and service managers.• Applying different machine learning techniques (e.g. NLP, classification, outlier detection) to data and analytics problems within the insurance industry.
• Collaborating closely with a team of expert data scientists to bring state-of-the-art machine learning models to production.
• Supporting the end-to-end management of the model lifecycle including DevOps practices and CI/CD capabilities.
Taking responsibility for using cloud technology, machine learning and data to enable the productivity of our clients.
• Very good experience with implementing machine learning and deep learning applications as well as building production quality and large-scale deployment of applications related to machine learning.
• Very good Azure technology skills in multiple Azure services (incl. Azure Machine Learning).
• Proven capabilities to develop, maintain and serve machine learning models on infrastructure.
• Strong skills in big data technologies (e.g. Spark) and operationalization technologies (Docker, Kubernetes, CI/CD).
• Experience with algorithms, data structures, and object-oriented programming (e.g. Python, PowerShell, Bicep, ARM).
• Familiar with collaboration tools (e.g. git, Azure DevOps).
• Strong knowledge of machine learning techniques (e.g. KNN, random forest, Bayesian statistics) and of Cloud-Native Architectures, preferably in Azure.
• Experience with R and/or Python applied to machine learning.
• High level of commitment and flexibility in terms of area of assignment in the section, and a willingness to master a wide range of what are sometimes complex tasks.
• Fluent spoken and written business English (German highly appreciated).
• BDAP program is about 30 team members (dev and run)
• DevOps mode
• Agile working environment (relay, sprint planning, dailies, scrum master,…)