Associate Director, Oncology Data Science
AstraZeneca
- Mississauga, ON
- Permanent
- Full-time
Mississauga, OntarioJoin our Early Data Science team in the Oncology R&D department at AstraZeneca, where we are growing to meet the strategic challenges pursued by AZ Oncology. We are looking for a talented and highly motivated Associate Director of Data Science to join a team designing and applying cutting-edge computational analysis to drive clinical biomarker hypothesis, and advance our understanding of response and resistance mechanisms of novel therapeutics.Accountabilities:As an Associate Director, you will apply advanced statistical and machine learning methods to analyze multi-modal data aiming to potential biomarker and MoA (mechanism of action) insights. You will drive the development of biomarker identification, validation and patient stratification strategies in collaboration with cross-functional teams. You will effectively communicate complex findings and recommendations to diverse stakeholders through compelling data visualizations, reports, and presentations. You will also work with our Research and Translational Medicine Leads to proactively influence the generation of data assets as part of a data generation strategy to evaluate novel hypothesis and drive target discovery.Essential Skills/Experience:
- PhD in Data Science, Statistics, Bioinformatics, Computer Science, or a related quantitative field, with more than three years of experience in Pharma/Biotech or large cancer center
- Extensive expertise in statistical analysis, machine learning, and advanced data manipulation techniques
- Proficiency in programming languages such as Python, R, or similar
- Significant experience in cancer biomarker analysis of multi-modal data from oncology clinical trials
- Deep knowledge of cancer genetics and key algorithmic & statistical methods applicable to cancer genomics
- Exceptional communication and leadership skills
- The ability to coordinate and pursue multiple simultaneous projects with tight deadlines
- Strong external presentation and publication record
- Experience working with spatial omics data
- Proficiency in generative AI techniques and their application in data analysis and research
- Well networked within external data science and oncology communities