Apply statistical methods to detect anomalies, trends and shifts. Your Profile BSc/MSC/Ph.D Degree in Mathematics, Computer Science, Information Technology, Physics or Engineering.At least 5 years experience in the field of data analytics, data mining.Technical expert in the field of data analytics, data mining.Proficient in Python and SQL languages.Experienced with statistical modelling and data mining techniques.Strong problem-solving skills with ability to multi-task and manage multiple projects simultaneously.
Werden auch Sie ein Teil der erfolgreichen MBDA-Gruppe. WAS SIE BEITRAGEN KÖNNEN Sie studieren aktuell Informatik, Computer Vision, Statistik oder Data Analytics und sind an einer spannenden Werkstudententätigkeit interessiert? Sie interessieren sich für verschiedene Methoden aus den Bereichen Statistik und Data Mining?
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.