Principal Statistician

Summary

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.

Core Competencies & Responsibilities

Discovery & Translational

• Documents projects in sufficient detail for reproducibility.
• Serves as initial consultation contact for new projects. Maintains and grows customer base, and builds loyal relationships with customers.
• Assumes independent, professional responsibility for all phases of a project request from beginning through completion, with minimal supervision as needed.
• Manages multiple projects.
• Leads Statistical Input for at least one functional area, research field, or compound.
• Provides input to product development and performs statistical functions for submission related activities where appropriate.

Statistical Modeling & Methodology

• Support broad implementation of innovative statistical approaches across the development portfolio.
• Support development and implementation of innovative approaches, participating in their hands-on implementation through direct interactions with statisticians. This involves, but is not limited to, identifying appropriate designs and methods, decision rules (e.g., Go/No Go); planning, running, and summarizing simulation studies to evaluate the operating characteristics of alternative designs and methods under a range of scenarios; and participating in the implementation of the selected approaches by engaging in protocol and SAP write-up.
• Collaborate with external consultants to provide support in the development and implementation of innovative methods and designs.
• Identify opportunities for innovation; interact directly with statisticians and other QS scientists for early identification of opportunities for innovative approaches.
• Participate in training and presentations on innovative approaches across the R&D organization (including statisticians, pharmacometricians, clinicians, and other stakeholder groups) to ensure awareness and adequate knowledge about these methods. Keep up-to-date knowledge of designs and analysis methods for clinical trials, including adaptive designs, model-based methods, etc.
• May engage in external collaborations within professional associations (e.g., ASA, IBS, SCT, ISoP, ISCB, PSI, EFPSI), participating in working groups, program committees, organizing sessions and presenting at scientific meetings, and publishing in peer reviewed journals.
• Knowledge of biostatistics applied to clinical trials and model-based drug development.
• Some experience with planning, running, and documenting simulations (including, but not limited to clinical trial simulations).
• Awareness of Bayesian methods and inference.

Manufacturing & Toxicology

• Documents projects in sufficient detail for reproducibility, including entry in project tracking systems and placement into shared repositories.
• Serves as initial consultation contact for new projects. Maintains and grows customer base, and builds loyal relationships with customers.
• Assumes independent, professional responsibility for all phases of a project request from beginning through completion, with minimal supervision as needed.
• Manages multiple projects.
• Leads Statistical Input for at least one functional area, research field, or compound.
• Provides input to product development and performs statistical functions for submission related activities where appropriate.

Medical Affairs

• Provides critical statistical oversight to Medical Affairs clinical studies and assumes a leadership role in clinical trial and/or patient registries planning (mostly Phase 3b/4 trials or observational studies for post marketing commitments/requirements) and reporting related activities; assumes the role of a Statistics representative for cross-functional teams and works on several trials (projects) simultaneously.
• Provides statistical input for clinical trials, observational studies and other types of clinical research projects including but not limited to post-hoc analyses, investigator initiated studies, publications, and HECOR/Epidemiology/Market Access support; Contributes/leads clinical study design, analysis planning and for the development of statistical analysis plan (SAP) and data presentation plan (DPS) for MA studies; Provides input to product development and performs statistical functions for submission related activities; Provides statistical support to other disciplines related to clinical statistics (e.g., HECOR/Epidemiology and publication activities); May serve as a primary contact with outside investigators (and vendors)in the preparation of scientific presentations and manuscripts; may interact with external Key Opinion Leaders (KOLs) and pursues rigorous statistical analyses in support of business-critical new research ideas; Explores and implements innovative statistical methods; Represents department in meetings with regulatory agencies.

Real World Evidence

• 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.