Company Overview:
Beam Therapeutics is a biotechnology company committed to establishing the leading, fully integrated platform for precision genetic medicines. To achieve this vision, Beam has assembled a platform with integrated gene editing, delivery and internal manufacturing capabilities. Beam’s suite of gene editing technologies is anchored by base editing, a proprietary technology that is designed to enable precise, predictable and efficient single base changes, at targeted genomic sequences, without making double-stranded breaks in the DNA. This has the potential to enable a wide range of therapeutic editing strategies that Beam is using to advance a diversified portfolio of base editing programs. Beam is a values-driven organization committed to its people, cutting-edge science, and a vision of providing life-long cures to patients suffering from serious diseases.
Position Overview:
Beam is seeking an Associate Director/Director of Biostatistics to provide the statistical strategic plan, design, execution, and reporting of clinical trials across Beam’s development programs. The ideal candidate will work closely with the Head of Biometrics and play a key role in the statistical strategy for clinical development programs and provide oversight to CROs to ensure timely execution of the clinical trials.
Responsibilities:
- Responsible for the statistical strategy for one or more clinical programs/studies and for providing oversight of CRO biometrics deliverables.
- Support clinical development team to enable robust study design and execution with a focus on innovative and efficient quantitative decision making.
- Contribute to clinical protocol development, including design evaluations and authoring of protocol statistical sections.
- Work with study team to develop SAP, data specification, TLF shells, and data monitoring charters etc. and generate TLFs and perform ad hoc analysis as needed.
- Review CRF design, data management plan, and data transfer plans to ensure data collection meet the trial objectives and requirements of statistical analyses.
- Specify randomization schedules and test their implementations as needed.
- Contribute to the review and interpretation of data analyses from clinical trials and to the development of CSRs, regulatory documents and support publications, manuscripts, posters and abstracts.
- Support regulatory submissions and interactions with regulatory agencies.
- Provide requirements and oversight to statistical programmers.
- Works collaboratively and communicates effectively with Statistical programming, Data Management, clinical operations, clinical development, Regulatory and other functions.
Qualifications:
- Ph.D. in statistics or biostatistics with a minimum of 7 years’ post-doctoral experience in pharmaceutical/biotech industry with prior project leadership or equivalent experience.
- In-depth knowledge of statistical methods and trial designs for rare disease and/or gene and cell therapy clinical trials.
- Extensive experience in statistical simulations, Bayesian statistical design and analysis and experience in observational studies and/or real world data (RW) are desirable.
- Extensive experience in NDA/BLAs, MAAs and other regulatory interactions preferred.
- Strong knowledge of FDA and ICH regulations and guidelines, experience and knowledge of gene/cell therapy are desirable.
- Proficient in SAS and R programming.
- Strong knowledge of data standards, including CDASH, SDTM, and ADaM.
- Must be self-motivated, and able to work independently and effectively with colleagues and vendors and demonstrate excellent verbal and written communication skills.
- Ability to prioritize and manage timelines and shifting priorities within a fast-paced company environment.
- Ability to build cross-functional relationships and work collaboratively across functions.
- Onsite requirements: Candidates are expected to come onsite approximately 2 days per week.
The salary range below reflects the full-time base salary range we expect to pay for this role at the time of posting. Base pay will be determined based on several factors including, but not limited to, relevant experience, education, scope of job, internal comparisons, and market data.
