Associate Director, RWE Data Scientist-Gaithersburg, MD

Do you have expertise in and a passion for Medical Affairs in Oncology? Would you like to apply your expertise to impact the Associate Director, RWE Data Scientist role at a company that follows the science and turns ideas into life-changing medicines? Then AstraZeneca might be the place for you! 

At AstraZeneca, we put patients first and strive to meet their unmet needs worldwide. Working here means being entrepreneurial, thinking big, and collaborating to make the impossible a reality. If you are swift to action, confident in your leadership, willing to collaborate, and curious about what science can achieve, then you’re our kind of person. 

AstraZeneca’s vision in Oncology is to help patients by redefining the cancer treatment paradigm, with the 2030 oncology ambition to have medicines that can potentially treat at least half of all cancers.  Our broad pipeline of next-generation medicines is focused principally on five disease areas: breast, lung, liver, ovarian, and hematological cancers. In addition to these tumor types, we are targeting cancers through five key platforms: immunotherapy, the genetic drivers of cancer and resistance, DNA damage repair, HER2, and antibody-drug conjugates, all underpinned by personalized healthcare and biomarker technologies. 

The Role 

The Centre for Oncology Data Excellence (CODE) is a function that is focused on delivering best in class scientifically rigorous research to support the Global Medical Evidence Generation.  Within CODE, Oncology Data & Analytics (ODA) is a key team responsible for RWD analysis, Data Foundation & Governance, Analytics Platforms and Tools and innovative AI capabilities.  The study execution within ODA is used for answering key clinical questions, and where applicable, supporting payer or reimbursement submissions.

As a member within the ODA team, your collaboration will span across multiple functional stakeholders within Medical Evidence Generation.  The ideal candidate for this role will bring a proven track record of delivering value through the utilization of routinely collected data from healthcare settings, providing health analytics and insights in various contexts, including Public Health, Pharmaceutical Research and Development, and Commercial/Payer sectors. They will collaborate with colleagues in Oncology Outcomes Research (O2R), Epidemiology and Statistics to provide scientific and technical guidance on study design, real-world data (RWD) selection, and best practices in RW data utilization.  With the rapid development of Generative AI, this role will drive the development and expansion of our GenAI and Agentic AI capabilities. 

Typical Accountabilities 

• Collaborate with Oncology Outcome Research (O2R) team to maximize the value derived from a variety of real-world data sources, including EMR, claims, registry and primary observational data. 

• Support stakeholders within Medical Affairs in providing access to analytical tools and developing visual analytics to enable self-serving applications for end customers. 

• Maintain a strong insight into the capabilities of in-house RWD to facilitate data source selection for RWE and insights generation.  
• Provide clear technical input, options, and direction to RWD analysis and utilization supporting 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. 
• Apply ML/AI techniques to analyse complex RWD, including the development of predictive models and algorithms to uncover patterns and insights in healthcare data such as EMR, claims, and observational data

Education, Qualifications, Skills, and Experience 

Essential: 

• PhD or MS in data science, epidemiology, statistics, artificial intelligence, computer science, or related field such as health informatics.

• Expertise in health data analysis, data visualization, methods development and application using statistical languages such as R, Python, SQL, or SAS. 

• Expertise in advanced visualization platform and visual analytics development, such as Shiny, Tibco Spotfire or Power BI. 

• Experience in real-world evidence and familiarity with health economics, epidemiology, observational study methodologies, and quantitative sciences such as health outcome modelling. 

• Expertise in EMR/Health I