Description
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 / AIML Engineer 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.
A core part of the work is proving out new methodology and capabilities on live client delivery, then partnering with engineering and product to productionize and scale what works. You will also contribute to AI/ML enablement proofs of concept that enhance existing offerings or shape new ones for our healthcare and pharma clients.
Responsibilities and Requirements:
- Develop ML solutions on large-scale medical data for disease detection and patient outcome prediction
- Translate client requirements for patient identification and HCP targeting into production analytics deliverables
- Prove out new methodology and capabilities on live client delivery
- Partner with engineering and product to productionize and scale what works
- Contribute to AI/ML enablement proofs of concept
Must-have requirements:
- 4-8 years of relevant experience in Data Science / Machine Learning
- Experience in Healthcare, Pharma, or Life Sciences
- Experience developing machine learning algorithms and predictive models
- Strong knowledge of statistics and supervised ML methods (e.g., regression, XGBoost, SVM)
- Strong Python skills (including OOP) for ML and ETL pipelines
- Experience with large healthcare datasets (Claims, EMR, consumer data)
- Experience with Git and software development best practices
- Experience mentoring junior team members
- Strong communication and stakeholder management skills
- Ability to work independently and collaborate in cross-functional teams