Senior Healthcare Data Scientist & ML Innovator

IQVIA Inc; Durham (NC); On-site; MXN 700,000 - 1,100,000; Full time

Job summary

IQVIA Inc. is seeking a creative Data Scientist / AIML Engineer to join our Healthcare Data Science team.

You will develop ML solutions on large-scale medical data for disease detection and patient outcome prediction, translating client requirements into production analytics deliverables. A core part of the work is proving out new methodology on live client delivery, then partnering with engineering to productionize and scale what works, while contributing to AI/ML enablement proofs of concept

Qualifications

• 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.

Responsibilities

• Support ML delivery and analytics delivery on large-scale medical data.
• Develop ML solutions for disease detection and patient outcome prediction.
• Translate client requirements into production analytics deliverables.
• Prove out new methodology on live client delivery and productionize scalable solutions.
• Contribute to AI/ML enablement proofs of concept for healthcare and pharma clients.

Skills

Python for ML

Statistics

Machine Learning

Communication

Team collaboration

Mentoring

Data preprocessing / ETL

Tools

Git

Job description

IQVIA Inc. is seeking a creative Data Scientist / AIML Engineer to join our Healthcare Data Science team.

You will develop ML solutions on large-scale medical data for disease detection and patient outcome prediction, translating client requirements into production analytics deliverables. A core part of the work is proving out new methodology on live client delivery, then partnering with engineering to productionize and scale what works, while contributing to AI/ML enablement proofs of concept