• Competitive
  • Redmond, United States
  • Permanent

Primary Responsibilities:

  • Provide expert support and guidance on data and statistical-related issues to the clinical team, actively participating in project team meetings when required.
  • Collaborate with the clinical team to contribute to the design of studies and development of clinical study protocols.
  • Work closely with internal or external data management teams, overseeing the design and review of CRFs, DTS, ECs, DVP, and actively participating in UAT and medical coding processes.
  • Generate and review data tables/listings, coordinating data review meetings to ensure the highest standards of data quality.
  • Conduct interim analysis, including statistical and pharmacokinetics analysis, to inform and support ongoing clinical decisions.
  • Develop and review Statistical Analysis Plans (SAP), including table/listing/figure shells, and participate in the review of final Statistical Analysis Reports (SAR) and Clinical Study Reports (CSR).
  • Oversee CRO programming activities, conducting quality assurance checks on internally or externally produced SDTM, ADaM, SAS tables, listings, and figures.
  • Ensure the quality control of project deliverables, verifying that outputs meet specified expectations.
  • Perform simulations and ad-hoc statistical analyses as needed to support project requirements.
  • Apply and adhere to regulatory guidelines and industry standards practices related to statistics and SAS programming.
  • Contribute to the generation and review of Standard Operating Procedures (SOPs) when required.

Education / Experience Qualifications:

  • Master’s Degree in Biostatistics, Statistics, or a related field is required.
  • Possess 3+ years of statistical work experience in academia or industry.
  • Demonstrate proficiency in statistical programming languages such as SAS, R, or Python.
  • Experience with CDISC and CDASH standards is essential.
  • Strong fundamental knowledge and practical experience in clinical trial design and data analysis, with the ability to effectively communicate statistical concepts.
  • Thorough understanding of applied statistics and data analysis methodologies, including regression modeling, categorical data analysis, survival analysis, etc.
  • In-depth knowledge of clinical research, the drug development process, and medical terminology, with a preference for experience in oncology.
  • Excellent oral and written communication skills, coupled with strong presentation abilities.
Sarah McGraw Division Manager

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