Formulates integrated analytical approaches to mine data sources, employs statistical methods and machine learning algorithms to address unmet medical needs, discover actionable insights, and automate processes to reduce effort and time for repetitive tasks. Manages the definition, implementation, and adherence to the data lifecycle of enterprise datafrom acquisition or creation through enrichment, consumption, retention, and retirementensuring the availability of clean, accurate data throughout its useful lifecycle. Independently sets strategy, manages budgets, and ensures appropriate staffing and project coordination within the area. Our Development Team is guided by our purpose: to reimagine medicine to improve and extend people''s lives. We are optimizing processes, investing in new technologies, and building therapeutic and platform capabilities to bring medicines to patients faster. We seek talented individuals like you to join us and help give people with disease and their families a brighter future. As an Associate Director of Data Science in the Medical Affairs Advanced Quantitative Sciences group, you will lead data science methodologies applied to patient-level dataclinical, real-world, and biomarker dataacross clinical development. You will combine your expertise in data science and AI with your scientific knowledge in biology or medicine to support drug development decisions in collaboration with internal and external partners.Contribute to planning, executing, interpreting, validating, and communicating exploratory analyses and algorithms to facilitate decision-making.Provide technical expertise in data science and machine learning/AI to identify opportunities influencing internal decisions and regulatory discussions.Perform hands-on analysis of integrated clinical trial and real-world data to generate evidence supporting decision-making in drug development.D. in data science, biostatistics, or a related quantitative field (or equivalent).Strong knowledge of statistical methods such as time-to-event analysis, machine learning, meta-analysis, mixed-effects and longitudinal modeling, Bayesian methods, variable selection techniques (e.g., lasso, elastic net, random forest), and clinical trial design.Proficiency in R and Python programming, with skills in data visualization, exploratory analysis, and predictive modeling.Why Novartis:

Join us to help people with disease and their families. Commitment to Diversity and Inclusion:

We strive to build an inclusive environment reflecting the patients and communities we serve.Join our Novartis Network:

Not the right role? Apache Spark, AI, Big Data, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Machine Learning, Python, R, Statistical Analysis#