The Team:
Our Data Science / ML team is a global group working at the center of IQVIA's advances in machine learning and applied statistical methods for real-world evidence. Our work spans disease detection, patient outcome prediction, retrospective clinical studies, and patient subgroups discovery.
We are looking for a creative, intellectually curious Data Scientist to join our Healthcare Data Science team. This role supports both ML delivery and analytics delivery: you will develop ML solutions on large-scale medical data for disease detection and patient outcome prediction and translate client requirements for patient identification and HCP targeting into production analytics deliverables.
Must-have requirements:
- 1-3 years of relevant experience in Data Science / Machine Learning
- Experience in Healthcare, Pharma Analytics, or Life Sciences
- Strong Python skills (EDA, feature engineering, model development)
- Hands-on experience with large healthcare datasets (Claims, EMR, consumer data)
- Machine Learning expertise (regression, classification, clustering, forecasting, predictive modeling)
- Solid statistics knowledge
- Experience with Git and coding best practices
- Strong communication and stakeholder management skills
- Ability to work independently and in cross-functional teams
IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com
IQVIA is committed to integrity in our hiring process and maintains a zero tolerance policy for candidate fraud. All information and credentials submitted in your application must be truthful and complete. Any false statements, misrepresentations, or material omissions during the recruitment process will result in immediate disqualification of your application, or termination of employment if discovered later, in accordance with applicable law. We appreciate your honesty and professionalism.