Maintain and troubleshoot data integration pipelines to ensure stable data flow into AI and analytics systemsSupport model development by assisting with training, validation, and optimization of machine learning workflowsConduct data analysis to extract insights and provide clear reports supporting R&D research questionsSolve technical challenges related to data access, pipeline performance, and software limitationsEnsure continuity of ongoing projects by aligning closely with the core team and delivering on timelinesPerform image analysis and prepare datasets required for scientific and ML use casesManage and improve ETL processes to ensure data quality, structure, and availabilityDocument workflows, pipeline changes, and analytical steps to ensure clarity and reproducibility Academic background in computer science, data science, engineering, or a related quantitative fieldStrong proficiency in Python with expertise in scientific and analytical librariesSkilled in SQL and working with relational databasesUnderstanding of ETL concepts and practical experience working with data pipelinesSolid foundation in machine learning principles and model lifecycleAbility to perform image analysis for scientific or research applicationsStrong communication and interpersonal skills with the ability to collaborate in a technical teamIndependent, structured problem-solver with a commitment to clear documentation and FAIR data practices Opportunity to contribute directly to active R&D projects with immediate real-world impactHands-on involvement in AI, machine learning, and data integration challenges in a scientific environmentClose collaboration with a small, highly skilled technical team Ihr Kontakt Referenznummer 863771/1 Kontakt aufnehmen Telefon:+41 44 225 50 00 E-Mail: positionen@hays.ch Anstellungsart Freiberuflich für ein Projekt
YOUR TASKS Design and maintain scalable data architectures and pipelines Collaborate with cross‑functional teams on data requirements Implement data quality and governance processes Drive adoption of modern data engineering technologies Guide and coach junior data engineers YOUR PROFILE Degree in Computer Science, Engineering or related field Minimum of 5+ years experience in data engineering, including architecture Expertise in ETL, Data Lakes and data warehousing Strong SQL, SSIS, SSAS and Azure SQL/databricks skills Experience with CI/CD (Azure DevOps, git) Programming skills in R, Python or Scala Very good English and strong collaboration skills YOUR BENEFITS Nordex offers a range of attractive benefits – here’s a selection of what you can look forward to.
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.
Takes a lead role in pro-active to suggest process improvement according WMS standards functionalities and business requirements Requirements: Bachelor or higher degree in Engineering, Computer Science, IT or Logistics. 4+ years’ experience in WMS implementations as functional analyst Strong knowledge in WMS solution Knowledge of integration techniques using middleware.
What You’ll Do: Collaborate in an Agile, International TeamWork closely with colleagues from Romania, Germany, and UkraineDesign, estimate, develop, and implement software solutions aligned with business needsActively communicate progress, risks, and technical decisions to stakeholdersBuild Scalable Data SolutionsDevelop agnostic data products within a modern, cloud-native data ecosystemSupport use cases across BI, Advanced Analytics, AI, and MLTranslate business requirements into robust technical architecturesContinuously enhance performance, quality, and cost-efficiency of solutionsProactively suggest improvements and best practices What makes you stand out Degree in Computer Science, Economics, or a comparable qualificationMinimum 3 years of experience as a BI Engineer or Data Engineer, focused on cloud-based architecturesStrong expertise in: Snowflake and DBT (Data Build Tool)Solid knowledge of: SQL and Data lakehouse architectures, Python is nice to haveCommunication is Key Excellent communication skills in English (written and spoken) — mandatoryAbility to clearly explain technical concepts to both technical and non-technical stakeholdersStrong stakeholder management and collaboration skillsComfortable working in cross-border, multicultural teams We are looking forward to your application and to applicants who enrich our diverse culture!
Tätigkeiten: Potenziale erkennen: Analysiere Kundenanforderungen und entwickle datengetriebene Lösungen – von Analytics über Machine Learning bis GenAI.Strategien entwickeln: Konzipiere individuelle Data-&-AI-Strategien für vielfältige Use Cases.Lösungen skalieren: Entwirf zukunftsfähige Architekturen für Datenplattformen, ML-Pipelines und AI-Systeme.Technologien prüfen: Teste und empfehle passende Technologien, begleite Umsetzungsteams mit klaren Roadmaps.Business ausbauen: Unterstütze Pre-Sales-Aktivitäten, Marktanalysen und die Weiterentwicklung datenbasierter Geschäftsbereiche.Angebote mitgestalten: Bringe deine Ideen in Lösungskonzepte, Kalkulationen und Präsentationen ein.Akademischer Hintergrund: Erfolgreich abgeschlossenes Studium der (Wirtschafts-)Informatik, Computer Science oder eine vergleichbare Qualifikation.Erfahrung: Mehrjährige Erfahrung in der Konzeption und Umsetzung moderner Datenplattformen, ML-Lösungen und AI-Systeme.Technologiekompetenz: Fundierte Erfahrung mit Azure, Databricks oder AWS sowie in Python, SQL, Docker, CI/CD-Pipelines und Infrastructure as Code.Fachliches Know-how: Tiefes Verständnis moderner Datenarchitekturen, MLOps und Data Governance.Arbeitsweise: Kombination aus konzeptioneller Stärke, analytischem Denken und pragmatischer Hands-on-Mentalität.Kommunikationsstärke: Fähigkeit, komplexe Themen klar und überzeugend zu vermitteln – in Deutsch und Englisch.Flexibilität: Wir bieten dir flexible Arbeitsmodelle mit großzügiger Gleitzeitregelung – wahlweise an einem unserer Standorte oder bis zu 100 % mobil innerhalb Deutschlands.Einarbeitung & Entwicklung: Deine individuelle Einarbeitung und Karriereförderung liegen uns am Herzen.