As part of our team, you will take on the following responsibilities: You are the driving force that transforms innovative AI/ML concepts from the lab environment into robust, scalable products — ensuring prototypes evolve into stable, production‑ready systems.You operationalize the entire ML lifecycle, developing automated CI/CD pipelines, taking ownership of deploying models into production, and continuously expanding our resilient MLOps infrastructure.You implement algorithms and complex feature transformations efficiently within production systems, optimizing them for latency, throughput, and maximum stability.You build scalable data pipelines and feature stores that ensure reliable, consistent data supply for both training and serving — online and offline.You establish professional monitoring mechanisms such as drift detection, automated retraining, and validation processes to guarantee long‑term model quality in live operations.You collaborate closely with Data Scientists, MLOps teams, and IT Infrastructure teams, ensuring that all production‑grade AI/ML solutions follow software engineering best practices and comply with security, privacy, and regulatory requirements. What makes you stand out You hold a master’s degree in Computer Science, Software Engineering, Mathematics, Statistics, or a related quantitative field.You have at least 3 years of professional experience in ML Engineering or MLOps, with a proven track record of building, deploying, and operating tailored AI/ML solutions in production.You bring deep expertise in Python and SQL, hands‑on experience with cloud platforms (ideally Azure), and familiarity with data warehouses such as Snowflake; foundational knowledge of Infrastructure‑as‑Code tools like Terraform is a plus.You are proficient with CI/CD tools (e.g., Azure DevOps), containerization technologies (Docker/Kubernetes), and apply modern software design patterns confidently.You thrive in a dynamic, agile, and innovative environment, working effectively both independently and as part of a team.You possess excellent English communication skills, both written and spoken; German language skills are considered a plus.
What makes you stand out You hold a Master’s degree in Economics, Mathematics, Statistics, Computer Science, or another related quantitative field.You bring at least 3 years of professional Data Science experience and have a proven track record of bringing models from the lab into real‑world production use cases.You are proficient in Python and SQL and have hands‑on experience building solutions on Azure and working with Snowflake.You have a deep understanding of statistical methods and apply them effectively in an agile, fast‑paced environment.You think in products, not experiments – model versioning, testing, and performance monitoring are second nature to you.You communicate complex topics clearly and with impact, presenting to different audiences confidently; you are fluent in English, and German skills are a plus.
Delight customers by providing outstanding technical support, service, and product selection assistance. Responsible for maintaining company property (company car, computer, office equipment, customer demo/loaner products, consignment stock, etc.) that is in his/her control, and or at his/her customer site.
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.