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About Johnson & Johnson
Johnson & Johnson is a multinational corporation operating in three main segments: consumer health products, pharmaceuticals, and medical devices, known for brands like Tylenol, Band-Aid, and Janssen. Industry: Pharmaceuticals & Medical Devices
Johnson & Johnson currently has
49 open roles
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JOB TITLE: Associate Director, Global Real-World Evidence, Immunology
The Associate Director, Global Real-World Evidence, Immunology joins the Innovative Medicine team to support the development and execution of global real-world evidence strategies across the immunology portfolio. This role involves translating asset and disease-area priorities into high-quality studies that support market shaping, medical adoption, and evidence-based decision-making. Key responsibilities include developing integrated evidence generation plans, managing stakeholders, and overseeing the execution of priority studies. The successful candidate will utilize expertise in epidemiology, pharmacoepidemiology, and health economics to analyze real-world data sources like claims databases, electronic health records, and registries. Required skills include observational study design, bias mitigation, and project management. Preferred technical proficiencies include SAS, R, and Python. This position addresses the business problem of generating timely, scientifically rigorous evidence to inform immunology product strategy and reimbursement.
Develop and maintain Integrated Evidence Generation Plans and long-range Worldwide RWE Roadmaps for assigned disease areas.
Drive the execution of high-priority RWE studies to ensure timely delivery and scientific rigor.
Translate study concepts into protocols, analyses, deliverables, and publications in collaboration with cross-functional partners.
Serve as a methodology subject matter expert on real-world data sources, observational study designs, and analytic approaches.
Analyze and synthesize real-world data, literature, and competitive evidence to inform strategic decision-making.
Manage global and regional stakeholders across cross-functional workstreams, RWE Working Groups, and project execution forums.
Oversee operational governance, including resource planning, deliverable tracking, vendor oversight, and process consistency.
Ensure all RWE activities comply with regulatory, legal, privacy, and publication requirements.
What we're looking for
An advanced degree in epidemiology, pharmacoepidemiology, health economics and outcomes research, public health, biostatistics, health policy, health services research, or a related field is required.
A PhD is preferred.
A minimum of 5 years of relevant experience in the pharmaceutical, biotechnology, consulting, academic, or healthcare environment is required.
Demonstrated experience supporting the design and execution of RWE studies, including observational studies, retrospective database analyses, and protocol development is required.
Strong working knowledge of real-world data sources, including claims databases, electronic health records, registries, and chart reviews, is required.
Experience collaborating with programmers, statisticians, and external vendors to execute data-driven research projects is required.
Hands-on experience with SAS, R, Python, or other statistical programming tools is preferred.
Experience contributing to publications, congress presentations, or other scientific communication outputs is required.
Remote (Raritan, NJ)+321 days ago
$137,000–$235,750
Data Science
Real-World Evidence
Machine Learning
Predictive Modeling
Statistics
Bioinformatics
Epidemiology
Computational Biology
Electronic Health Records
Administrative Claims
R&D
Digital Health
Real-World Data
Artificial Intelligence
Machine Learning
Generative AI
Data Science
Advanced Analytics
Data Strategy
HIPAA
GDPR
Data Product
Market Intelligence
Federated Environments
R
Python
SAS
Data Science
Real-World Evidence
RWE
Biostatistics
Epidemiology
Data Extraction
Statistical Analysis
EHR
Insurance Claims
Registry Data
Clinical Trial Data
Econometric Models
Data Visualization
Real-World Data
R
SAS
Python
Biostatistics
Epidemiology
Observational Study Methodology
Data Governance
FAIR Principles
Agile
Pharmacoepidemiology
HEOR
Advanced Analytics
Data Science
Clinical Data Strategy