Associate Director, MedTech Epidemiology and Real-World Data Sciences

About the role

The Johnson & Johnson MedTech Epidemiology and Real-World Data Sciences (MedTech EPI-RWDS) team provides analytical capabilities using large administrative, patient-level databases to answer a variety of questions related to safety, product development, health outcomes research, and other clinical or commercial activities.

Key Responsibilities

• Lead and contribute to the design of observational database analysis, including authoring protocols and analysis plans in support of RWE needs for the MedTech Cardiovascular franchise.
• Lead the synthesis of evidence from observational database analyses with other evidence to inform medical decision-making, including authoring publications and presentations.
• Work closely with colleagues within the department and across the larger cross-sector Epidemiology function, health economics and market access (HEMA) function, clinical function, and other Cardiovascular medical device functions.
• Implement new approaches for working with “big data” in healthcare. Some tasks may include data visualization, predictive analytics and machine learning algorithms.
• The position will report to the Senior Director, MT EPI-RWDS.

Qualifications

• A Doctor of Philosophy (PhD) Degree or equivalent in biostatistics, health services & outcomes research, epidemiology or other healthcare-related field with a minimum 3 years of epidemiology or related professional research experience. (Highly qualified candidates with a Masters degree may be considered.)
• In-depth knowledge of healthcare databases, registries, statistical analysis, and other related analytical methodology is required.
• A sophisticated understanding and the ability to analyze and interpret quantitative data.
• Experience with writing methods sections of study proposals and protocols is required.
• Experience authoring peer-reviewed publications and presenting in national/international healthcare conferences using results from real-world datasets is required.
• Experience in cross-functional partnering is required.
• Consulting, pharmaceutical or medical device industry experience is preferred.