Data Scientist, Full-Time (f/m/d)

Tasks

• Define and maintain the end-to-end technical vision, roadmap, and priorities for the Data Science department across the company's platform and data analytics teams.
• Monitoring of requirements and transformations, including well-formed and correct data processing; the accuracy and consistency of the results are essential standards.
• Ensuring excellent quality, reliability, consistency, and security in technical solutions (e.g., MLOps, comprehensive governance), establishing a proven level of control and high performance, while continuously monitoring, adapting, and improving the necessary measures.
• Collaborate with stakeholders to define and establish goals (e.g., data usage metrics) and assign responsibility to teams within the company's business units.
• Managing the business by collecting, mapping, and ensuring data quality.
• Ensure the delivery and management of data science services provided to the company’s internal and external stakeholders.
• Establishing and monitoring SLAs and SLOs, as well as managing internal service teams (e.g., regression, health checks) between stakeholders and data science teams.
• Ongoing professional development and training (e.g., through the company's internal data science channel).
• Ensure that solutions and processes are in place to establish trustworthy data science, governance, and compliance (e.g., compliance and maintenance of data processing, information technology, and data).
• Ensure the rollout of large-scale data projects and contribute to data science capabilities (e.g., governance, automation), AI capabilities, and model development, as well as the automation or expansion of the platform.
• Organizing or participating in workshops, seminars, and training sessions on various topics to share knowledge and experience with the data science department and other departments.
• Contribution to the development of new data science tools and methods.
• Supporting the data science team in implementing new projects.
• Providing technical support for the development of data science products.
• Contributing to the continuous improvement of data science processes.
• Providing training and coaching for the data science team.
• Building an online profile, documenting and verifying data science and AI expertise, which is developed and managed through integrated data analysis and a data lake.
• Assistance in improving key data science and AI components for products and implementing a problem-based architectural transformation.
• Development of sample training materials and guidance on how to adapt them to real-world practice.
• Pursuing an expanded initiative and development efforts to create training content.
• Actively contributing to the technical vision and framework of the data science team.
• Developing and managing data science roadmaps and fostering a data-driven culture.
• Promoting end-to-end development activities in lean teams (by institutions and by improving platform performance and quality within an IT and digital team).
• Ensuring technical leadership and continuous product cycles, as well as iterative data science solutions with a long-term commercial foundation.

Requirements

• A bachelor's or master's degree in computer science, information systems, or a related field (e.g., mathematics), or a combination of academic knowledge and more than five years of professional experience in the areas mentioned above.
• Advanced expertise in multiple programming languages (e.g., SQL) and statistics (e.g., scikit-learn).
• Experience with cloud services (e.g., Azure) / cloud-native architecture (