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Principal Statistician

Posted on Apr 5, 2021 by Johnson & Johnson

Raritan, NJ 08869
Retail Trade
Immediate Start
Annual Salary
Full-Time


Job Description
The Principal Statistician supports the design, execution, analysis, interpretation, and reporting or communication of data evidence for Pre/Early/Late Clinical Development, Research & Discovery, Medical Affairs, Real World Evidence, or Manufacturing Sciences programs for research, development, and/or marketed product needs in Janssen, with minimal supervision. This position supports statistical aspects of business-critical and/or regulatory commitments, provides input to program plans with limited supervision, and represents Statistics & Decision Sciences (SDS) for cross-functional and intra-departmental teams or working groups. He/She abides by the Credo and practices J&J Leadership Imperatives for Individuals: Lead, Shape, Connect, and Deliver.
The succesful candidate will demonstrate advanced data analytic expertise based on a foundation of statistical principles and a strong track record of applied experience leading to successful program support. Is effective in the use of relevant computational tools for study, experiment, or trial research objectives. Applies high quality statistical methodology in assigned projects with demonstrated understanding of the disease/scientific/functional area and health authority acceptability.
She/He will demonstrate thorough knowledge of pharmaceutical research and development strategies and execution. Takes a lead in providing SDS support to experimental design, modeling, analysis planning, analysis execution, interpretation, and statistical communications. Is accountable for execution of individual project responsibilities, including: meetings with necessary project team members, reporting activities, exploratory analyses/graphics, and additional analyses to support publications for individual clinical trials/studies/projects. Is an evolving leader for providing input to team in terms of optimizing study or trial designs in line with study or indication level objectives, and supports scenario simulations and sample size calculations based on relevant technical and disease/scientific/functional area knowledge.: Demonstrates thorough knowledge of pharmaceutical research and development strategies and execution. Takes a lead in providing SDS support to experimental design, modeling, analysis planning, analysis execution, interpretation, and statistical communications. Is accountable for execution of individual project responsibilities, including: meetings with necessary project team members, reporting activities, exploratory analyses/graphics, and additional analyses to support publications for individual clinical trials/studies/projects. Is an evolving leader for providing input to team in terms of optimizing study or trial designs in line with study or indication level objectives, and supports scenario simulations and sample size calculations based on relevant technical and disease/scientific/functional area knowledge.
They will proactively interface with clinical teams to identify opportunities where real-world data analysis can support the clinical development feasibility assessment; Serve as liaison between the TA Clinical Teams and the Epidemiology Analytics Team to facilitate the translation of protocol Inclusion/Exclusion criteria into meaningful data definitions, and to track and measure outcomes; Work with RWE Feasibility Lead to shape and influence the future of protocol development through the use of novel technology applied to real world data to enhance data-driven operational decision making; Work closely with key stakeholders, including the Study Placement & Analytics group and the Clinical Program Leader, to run RWE analysis that support protocol design and protocol feasibility.
Qualifications
Ph.D. in Statistics or related field with minimum 2 years relevant experience, or Master's in Statistics or related field with commensurate years of relevant experience.
Proficient in SAS or R programming.
Ability to work independently.
Demonstrated ability to work in interdisciplinary contexts outside statistics




Reference: 1152697152

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