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. Our Ideal Candidate Will Have: Master’s degree in Computer Science, Mathematics/Statistics, Economics/Econometrics or related field.Substantial years of professional experience in quantitative data analysis or PhD with at least 1 year of relevant professional experience with research in machine learning algorithms.Very good knowledge and in depth understanding of Machine Learning methods, both classical and deep learning models.Relevant experience with Natural Language Processing (NLP) models for extracting structured concepts from unstructured free text, including the design, training, and evaluation of information‑extraction pipelines.Very strong technical capability in Python, SQL, Hadoop ecosystem.Experience applying AI/Machine Learning methods to business questions.Very good knowledge of the higher statistical and econometric methods in theory and practice.Experience with handling Big Data.Ability to write clean, reusable, production-level codeExcellent communication skills (written and oral) including technical aspects of a project, ability to develop usable documentation, results interpretation and business recommendations.Strong analytic mindset and logical thinking capability, strong QC mindset.Knowledge of pharmaceutical market and experience with pharmaceutical data (medical, hospital, pharmacy, claims data) would be a plus, but not a must.Self-responsible for managing projects.Fluency in German & English.
What makes you stand out You hold a degree in Business Informatics, Data Science, Computer Science, Industrial Engineering, Business Administration, or a comparable field.You have several years of experience in building, operating, or further developing data‑driven products—ideally in a sales, marketing, or customer service context.You have solid knowledge in designing and developing cloud‑based data products such as data warehouses, semantic layers, analytical models, and reporting and analytics solutions.You possess strong knowledge of data architectures, data engineering, data science, and data governance.You bring experience in leading interdisciplinary teams both functionally and disciplinarily—ideally including Data Engineers, Data Scientists, Product Owners, and Data Governance roles.You demonstrate strong analytical and conceptual thinking skills and the ability to prepare complex topics in a structured and understandable way.You communicate effectively and are able to bridge different target groups (business & tech).You work with strong execution and results orientation while ensuring high data quality.You have excellent German and English skills, both written and spoken.
Review operational costs, negotiate contracts with vendors, and manage vendor relationships. Requirements: Bachelor's degree in Engineering, Computer Science, or a related field. HV Authorised Person (Experienced with HV Systems) Electrical/Mechanical Engineering HNC or HND (Successfully completed apprenticeship in either) C&G Pts. 1 & 2, equivalent or exceeds. 17th Edition IEE: Wiring and Installation (Ability to attain 18th Edition through additional training) C&G 2391 test and inspection; BS 7671:2001 for inspection, testing and certification.
Responsible for all aspects of Material Master for the global template and for MDG-M Review all Requirements for clarity and for support of harmonized approach Drive, oversee, guide and assist the technical developers Test all requirement implementations Involved in all aspects of PLM Interfaces for each of the PLM Systems With each roll out the above topics must be addressed in different ways including migration With regards to migration: manage clones, collisions, duplicates for every S4E-Unify and Agora Roll Out Provide demonstrations on MDG-M functionality, oversee the Data Quality module and its implementation relative to KPI’s and management of KPI results Bachelor’s degree in computer science, Business Management, Management Information Systems or equivalent experience Experience in business process design in material management and production planning Expert knowledge about PP, MM, MDG-M, processes and customizing in SAP S/4 HANA Experience and the ability to read ABAP code / debugging are desirable Ability to meet business requirements through the standard solution used Excellent with troubleshooting and analytical skills 10-20% business travel (international and domestic) is expected Languages: English, German (optional) Exciting Global Projects: Be part of a major international SAP S/4HANA transformation program Hybrid Work Model: Flexible working hours and remote work options depending on project needs Professional Development: Opportunity to work with cutting-edge technologies and gain experience in SAP S/4HANA, MDG-M, and PLM interfaces International Environment: Collaborate with global teams across different countries and cultures Modern Workplace: Access to Siemens Energy’s innovative and sustainable office infrastructure Networking Opportunities: Work alongside experts in energy, digitalization, and transformation Gehaltsinformationen 120000 Ihr Kontakt Ansprechpartner Julian Hientz Referenznummer 847518/1 Kontakt aufnehmen E-Mail: julian.hientz@hays.de Anstellungsart Anstellung bei der Hays Professional Solutions GmbH