Senior Principal Biostatistician, Biometrics - Biosimilar Business Unit

Key Skills

Biostatistics, SAS, Statistical modeling

Job Description

• The Senior Principal Biostatistician is responsible for providing the statistical expertise for biosimilars, pre- and post-approval within one or more therapeutic areas.
• Responsible for all statistical aspects in the development, regulatory submission and post-approval lifecycle management of biosimilars.
• Represents BBU Biometrics as a core member of Clinical Development Teams (CDT) throughout development and regulatory assessment and leads analysis strategies of Real World Evidence (RWE) data and exploratory analysis to support post-approval publications.
• Contributes to the long-term growth strategy of the department by participating in process improvement initiatives, keeping abreast of the current statistical methodology development, and providing mentorship to new/junior biostatisticians.

Principal Accountabilities

• Acts as Project Lead Statistician (PLS) during the development and regulatory assessment phase of biosimilars, including:
  • Providing strategic input into the clinical development plan (CDP)
  • Providing statistical leadership as a member of the CDT
  • Defines statistical methodology, analyzes data, reports results and contributes to the strategic planning and execution of the CDP
• Supporting regulatory submission and assessmentLeads post-approval statistical strategy, analysis and reporting for RWE and Phase IV study data, including collaboration with external investigator-sponsors and KOLs.

• • Responsible for the design, planning and conduct of analyses of Phase IV clinical trials and observational studies as well as post-hoc analyses of existing databases and meta-analyses.
  • Generate publications, presentations, and posters in collaboration with Medical Affairs teams, present the work in conferences/congress.
  • Perform scientific appraisal of study protocols and study proposals.
  • Build up RWE data generation strategies, together with the pharmacovigilance team; partner with external organizations to build RWE datasets, perform the corresponding analysis for various scientific purposes.
• Contributes to the long-term growth and positioning of the function and as a SME for cross-functional understanding of biostatistics in the development of biosimilars:

• Serves as peer reviewer for material authored or coauthored by other statisticians and other clinical research personnel
• Acts as an internal consultant on broad statistical issues that impact pharmaceutical / biotechnology / biosimilars development
• Keeps up to date current on statistical methodology and computing development
• Represents Biogen in cross-company initiatives regarding statistics and/or the development of biosimilars
• Supports foundational understanding of biostatistics through the deployment of functional and cross-functional training and knowledge-sharing
• Supports BBU R&D continuous and process improvement initiatives

Qualifications

• PhD in Biostatistics/Statistics or equivalent with a minimum of 3-5 years relevant work experience or MS in Biostatistics/Statistics with a minimum of 5-7 years relevant experience.
• Very good understanding of theoretical and applied statistics, including but not limited to estimands, missing data and bio- equivalence trials.
• Ability to provide technical solutions to a wide range of difficult problems. Solutions are innovative, thorough and practicable, and consistent with objectives.
• Working knowledge of medical/biological terminology and clinical trial designs and competitive landscape in relevant therapeutic areas.
• Conversant with SAS or other software programming
• Working knowledge of regulatory guidelines and Commercial needs relating to statistical analysis, study reports and statistical components of regulatory submissions.
• Highly motivated and enjoying working in cross-functional matrix management teams (e.g. CDT).
• Able to manage multiple projects simultaneously, to manage conflicting priorities, and to be flexible when priorities change.
• Able to write and present information effectively. Demonstrates leadership skills with effective communication including being able to explain methodology and consequences of decisions in lay terms; able to translate requests to meaningful and relevant hypotheses/statistical questions.
• Knowledge and experience in real world science is a plus.