At AstraZeneca, we pride ourselves on crafting a collaborative culture that champions knowledge-sharing, ambitious thinking and innovation – ultimately providing employees with the opportunity to work across teams, functions and even the globe.
Recognizing the importance of individualized flexibility, our ways of working allow employees to balance personal and work commitments while ensuring we continue to create a strong culture of collaboration and teamwork by engaging face-to-face in our offices 3 days a week. Our head office and BlueSky Hub in downtown Toronto are purposely designed with collaboration in mind, providing space where teams can come together to strategize, brainstorm and connect on key projects.
Our dedication to sustainability is also central to our culture and part of what makes AstraZeneca a great place to work. We know the health of people, the planet and our business are interconnected which is why we’re taking ambitious action to tackle some of the biggest challenges of our time, from climate change to access to healthcare and disease prevention.

ESSENTIAL EDUCATION, SKILLS & EXPERIENCE:

• PhD or MS in data science or other advanced degree in life sciences such as epidemiology, or other training/work in Medical/Health Informatics/Biostatistics, or a related field.
• Expertise in data analysis, data mining, data visualization, methods development and application using statistical languages such as R, SAS, SQL, or Python.
• Expertise in advanced visualization platform and visual analytics development, such as Power BI and R Shiny.
• Experience in real-world evidence and familiarity with health economics, epidemiology, observational study methodologies, and quantitative sciences such as health outcome modeling.
• Expertise in EMR/Health IT, disease registries, and insurance claims databases.
• Experience in Statistical Analysis Plan (SAP) generation and execution for observational studies.

DESIRED EXPERIENCE & SKILLS:

• Expertise in clinical data standards, medical terminologies, and controlled vocabularies used in healthcare data and ontologies (ICD-9/10, NDC, HCPCS).
• Experience in supporting pharmacoepidemiology studies with a proven track record of advancing approaches with data science.
• Expertise in data mining approaches within healthcare settings to generate insights from routinely collected healthcare data.
• A history of patient care or equivalent background in a patient care setting that allows the candidate to bring a medical perspective into real-world evidence generation and observational studies.
• Demonstrated ability to build positive relationships, understand key challenges, and develop beneficial informatics projects.
• Ability to lead and manage multi-disciplinary data science projects.
• Strong track record of delivering large, cross-functional projects.
• Experience working in a global organization and delivering global solutions.
• Familiarity with the use of Machine Learning and Artificial Intelligence in the generation of hypotheses within Real-World Data

• Collaborate with Epidemiology and HEOR teams to improve the value derived from a variety of real-world data sources, including EMR, claims, and primary observational data.
• Support collaborators within Medical Affairs by providing access to analytical tools and developing visual analytics to enable self-serving applications for end customers.
• Provide clear technical input, options, and direction to RWD analysis and utilization supporting RWE and insights generation.
• Maintain a strong insight into the capabilities of in-house RWD to facilitate data source selection for RWE and insights generation.
• Help build a capability that becomes a source of sustained competitive advantage for AstraZeneca in identifying, acquiring, integrating, and mining diverse RW data from multiple geographic and healthcare system sources to support evidence generation and real-world studies.