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. 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.
Therapeutic area expertise in the field of Oncology is a must.Strong working knowledge of applicable clinical research regulatory requirements, i.e., Good Clinical Practice (GCP) and International Conference on Harmonization (ICH) guidelines.Fluent languages skills in German on at least C1 level and good command of English.Strong IT skills in appropriate software and company systems.Excellent decision-making and string financial management skills.Flexibility and ability to manage study teams in a virtual environment.Willingness to travel occasionally for business meetings.