Johnson & Johnson MedTech's Electrophysiology business needs to support critical evidence-generation activities through robust statistical analyses and innovative methodological applications to elevate standards of care for stroke, heart failure and atrial fibrillation (AFib) patients.
Requirements
- Deep knowledge of statistical inference, modeling, experimental design, Bayesian and frequentist methodologies.
- Experience with observational studies, causal inference, multiplicity adjustments, and Bayesian borrowing approaches preferred.
- Proficient in SAS, R, or equivalent statistical programming tools.
- Familiarity with regulatory processes and experience interacting with agencies such as the FDA is advantageous.
Responsibilities
- Provide expert statistical input for clinical trial design, analysis plans, and reporting, ensuring scientific rigor, regulatory compliance, and strategic alignment in support of device evidence generation.
- Independently develop statistical analysis plans for diverse phases of clinical studies.
- Review protocols and case report forms (CRFs) to ensure proper design and methodology.
- Perform data analysis, prepare statistical reports, and contribute to scientific publications and presentations, working closely with cross-functional teams and external partners.
- Support the preparation of documentation for regulatory submissions, including statistical sections, ensuring adherence to regulatory standards and guidelines.
- Stay current with advances in statistical methods, integrating them into study strategies as appropriate.
- Write comprehensive study documentation, statistical analysis plans, and reports.
Other
- PhD or Master’s degree in Statistics, Biostatistics, or related quantitative field.
- Minimum of 6 years of relevant experience in clinical research within Medical Device or Pharmaceuticals, with demonstrated expertise in statistical design, analysis, and reporting.
- Strong communication skills, with the ability to clearly convey complex statistical concepts.
- Present complex data analysis results clearly to technical and non-technical stakeholders.
- Collaborate effectively with cross-functional teams, external vendors, and regulatory bodies to ensure scientific and regulatory excellence.
