• Contract
  • Remote

SimulStat

– Remote
– 12 month renewable contract

 Core Responsibilities:
• Provide statistical guidance, review, and contribution to SAPs; TFL shells; DMC Charters; SDF specifications (SDTM and ADaM); randomization specifications; other key-study related documentation, protocol deviations, data quality review, and other communications
• Attend and be a contributor at Clinical Study Team Meetings
• Attend meetings for and provide statistical input into cross-functional study start-up activities, including but not limited to CRF development, database specifications review, database development, IVRS specification review
• Initiate cross-functional team meetings as necessary (e.g., analysis planning, TFL review)
• Complete statistical analysis of individual studies/projects
• Perform and document QC of primary and key secondary endpoints within ADaM datasets as well as the statistical analyses of these endpoints (programmatically)
• Perform data-driven modeling during clinical studies
• Create required outputs for DLRM meetings
• Review TFLs created by statistical programming for consistency and accuracy
• Author analysis reports such as Flash Memo, and results section of the CSRs
• Collaborate with the study programming team for study deliverables
• Manage timelines for all statistics-related deliverables for own projects and across projects for other study statisticians
• Be familiar with all Company’s policies, SOPs and other controlled documents related to study activities noted above
• Assist with study and systems audits conducted by Company GCA and external bodies

Minimum Education Required: Master’s degree in Statistics/Biostatistics or other subject with high statistical content with at least 4 years of post-graduate statistical experience in the pharmaceutical or biotech industry (or PhD degree with at least 3 years experience)
• Strong skill in communicating statistical information clearly and concisely (written and oral)
• Strong understanding of statistical concepts related to the design and conduct of clinical studies
• Strong ability to apply statistics in the analysis of clinical trials
• Independent leadership of the design, analysis and reporting of at least 1 complex or multiple less complex studies/projects within the Pharmaceutical/Biotechnology industry.
• Previous experience in the development, author, and execution of protocols and SAPs, as well as review of CSRs
• Excellent oral and written English communication skills
• Strong SAS and/or R programming skills in conducting simulations and applying statistical concepts and methods based on complex study designs

Preferred Qualifications:
• Master’s degree in Statistics/Biostatistics or other subject with high statistical content and at least 6 years of post-graduate statistical experience in the pharmaceutical/biotech industry OR Doctoral degree in Statistics/Biostatistics or other subject with high statistical content and 5 years of post-graduate statistical experience in the pharmaceutical/biotech industry 
• Designing, analyzing and reporting of clinical trials within Pharmaceutical/Biotechnology Industry 
• Demonstrated ability in presenting results and defending statistical findings, study design and analysis to internal audiences (study/product team) AND at external meetings such as investigator meetings, steering committee meetings, ad board meetings or regulatory meetings
• Leadership of at least 3 clinical studies/projects end-to-end with minimal oversight
• Life Cycle Drug Development Experience (Pre-clinical Development, Clinical Development, and Post-marketing)
• Demonstrated ability to work in cross-functional teams ideally including projects focused on delivering business solutions, working with clinical development colleagues in study management, programming and IS
• Demonstrated ability to influence decision making
• Experience in adaptive clinical trials and innovative study designs
• Experience in the utilization of Bayesian statistics in clinical trials
• Proficient SAS and R programming skills conducting simulations and applying statistical concepts and methods based on complex study designs

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