Senior Data Scientist (m/w/d)

Das ist der Job

Development of deep learning models for structured medical concept extraction from unstructured data.

Darum lohnt es sich

Frankfurt/Main, Germany | Full time | Hybrid | R1530250 Senior Data Scientist Data Science & Advanced Analytics Principal Accountabilities Collaboration in projects of the European Data Science & Advanced Analytics Team.

Application of modern data mining and machine learning techniques in connection with Healthcare Big Data to identify complex relationships and link heterogeneous data sources.

The Team Data Science & Advanced Analytics – with departments in Frankfurt, Philadelphia, Milan, Madrid, Athens, Warsaw and Beijing as well as a network of more than 300 experts worldwide – is the global competence center for statistics and data science at IQVIA.

The team is responsible for developments of the statistical procedures and methods used for quality assurance processes, data imputations, data projections, forecasting and many other healthcare panel data including pharmacy sales, ecommerce data, hospital consumption, physician level prescriptions and longitudinal anonymized patient level data. #J-18808-Ljbffr 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.

Productionalization of machine learning algorithms in Big Data platforms. 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. Ideal Candidate Qualifications 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 code.

Excellent 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.