Join Our Team Real-World Evidence in Immunology

Location: Remote, Spring House, PA, USA

At Johnson & Johnson, health is our top priority. We are at the forefront of healthcare innovation, working to prevent, treat, and cure complex diseases. Through our expertise in Innovative Medicine and MedTech, we deliver groundbreaking healthcare solutions to profoundly impact health for humanity.

Position Summary: Join our Real-World Evidence (RWE) team and apply advanced analytics to real-world data (RWD) in our Immunology group. This global role involves generating evidence that informs clinical development, regulatory strategies, and healthcare decision-making across diverse populations and geographies.
Key Responsibilities:
• Conduct impactful research using large-scale observational databases and clinical trial data.
• Collaborate with global cross-functional teams to design and execute studies.
• Develop protocols, statistical analysis plans, and programming specifications.
• Deliver high-quality outputs, including datasets, visualizations, and manuscripts.
• Present findings to global scientific and regulatory audiences.
• Stay updated with global trends in RWE methodologies and data privacy regulations.
Requirements:
• Masters in Epidemiology, Biostatistics, Data Science, Public Health, Biomedical Informatics, or a related field. PhD preferred.
• Experience with real-world data from diverse healthcare systems.
• Proficiency in R, Python, or SAS; familiarity with OMOP CDM and OHDSI tools is desirable.
• Strong communication skills in English; additional languages are a plus.
• Experience in Immunology.
• Experience in low- and middle-income countries.
Preferences:
• Experience with data sources from LMICs, including national health surveys and regional registries.
• Familiarity with LMIC health systems and global health policies.
• Experience with digital health technologies and AI-enabled diagnostics.
• Collaboration experience with pharmaceutical companies.
• Experience with international regulatory submissions.
• Knowledge of machine learning and advanced statistical modeling.
• Prior publications in peer-reviewed journals.

Duration: 1 year

Apply today to join our innovative team and make a global impact in healthcare!