What you can expect You take on the functional and disciplinary responsibility for all FTEs in the Sales Data Hub within the federated data setup, including Data Engineers, Data Scientists, Data Governance roles and Product Owners Data.You define, design, develop, and operate cloud‑based data products for the Sales, Marketing, and Customer Service business units.You are responsible for the methodological integration of data assets and data products.You manage the Sales Data Hub operationally and further develop it as a specialized unit for data‑driven solutions in Sales, Marketing, and Customer Service.You are responsible for the further development and ongoing maintenance of all sales‑related models based on feedback and requirements from the sales organization.You lead projects related to planning, expanding, and organizing new and existing products in collaboration with the relevant business units and external partners.You assume technical responsibility for data products developed by or for the Sales, Marketing, and Customer Service areas within the Data Intelligence & Analytics team.You drive the continuous expansion, professionalization, and organizational development of the Sales Data Hub within the existing governance and organizational framework.
DKV is the full‑service provider in the field of eMobility, offering tailor‑made solutions for electric vehicles: from charging infrastructure to planning and design, from consultancy to installation and electricity products. As a Customer Support Representative, you are the coordinator and take ownership of our service delivery.
You will support the automation analyst and designer during the technical generation and implementation phase, as well as supporting change management activities within the business function before and after go-live.
In this position you will work with applications engineers, product engineers and account managers to design and offer Leybold service and solutions that helps clients supercharge their process efficiencies. This position acts as the service sales liaison between the Leybold factory and the client with the intent to teach companies how to maximize the life cycle of their equipment through means of the VTS Service Ladder.
Your tasks As a Senior Automation Process Analyst (m/f/x) you will be involved in complex automation projects for at least one of the GBS business functions (e.g. Finance, HR, etc.). This entails developing a process design in close collaboration with process experts and automation designers, supporting the automation designer during the technical implementation phase, as well as supporting change management activities within the business function before and after go-live.
Furthermore, you will be accountable for standard and best practice setting, knowledge sharing and be involved in special projects (i.e. technology exploration). Automation projects comprise of developing a process design in close collaboration with process experts and automation designers, supporting the automation designer during the technical implementation as well as supporting change management activities within the business function before and after go-live.
Principal Accountabilities: Collaboration in projects of the European Data Science & Advanced Analytics Team.Concept, design, development and execution of complex innovative AI/Machine Learning solutions as well as execution and implementation of concept studies using advanced statistical methods.Development of deep learning models for structured medical concept extraction from unstructured data.Productionalization of machine learning algorithms in Big Data platforms.Application of modern data mining and machine learning techniques in connection with Healthcare Big Data to identify complex relationships and link heterogeneous data sources.Advanced usage of Large Language Models for summarization, chatbot, entity extraction etc.Develop foundational Deep Learning Models for assets and patients.Builds and trains new production grade algorithms that can learn from complex, high dimensional data to uncover patterns from which machine learning models and applications can be developed.