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Principal Scientist
Principal ScientistClinical Dynamix, Inc. • Waltham, MA, US
Principal Scientist

Principal Scientist

Clinical Dynamix, Inc. • Waltham, MA, US
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Principal Scientist (Contract to Perm); Hybrid in office 3 days per week

Description

Reporting to the VP, Clinical Pharmacology, the Principal Scientist will work with Discovery Research and Development team members, to support PPK / PKPD / ER dataset preparation and exploratory data visualization, across early and late-stage programs.

This role may be based in our Waltham, MA headquarters, which would be a hybrid role, or it can also be fully remote. Our office-based employees are required to work in the office three (3) days a week. If remote, travel to headquarters for meetings would be required at the discretion of management.

This role is a contract-to-hire position.

Responsibilities (including, but not limited to) :

  • Clean PK / Immunogenecity related datasets
  • Perform PK database lock
  • Transform the relevant STDM and ADaM datasets, and other sources of data to enable PPK, PKPD and ER analyses
  • Develop SAS (or R) codes to perform data visualization, descriptive statistical summary in TLFs
  • Ensure dataset formatted according to CDISC standard
  • Collaborate with biostatistics programmers, statisticians, and pharmacometricians, to ensure data consistency and accuracy for general PK, PK / PD and ER analyses
  • Stay informed with the emerging literature in programming approaches in PMx field
  • Maintain current understanding of global regulatory expectations for CDISC requirements

Requirements

  • Requires an MS or PhD or equivalent in educational background in Statistics, Mathematics, Informatics, Chemical engineer, Computer Science, Pharmaceutical Science, or a related field with 10+ (MS degree) or 5+ (PhD) years of clinical pharmacology related programming or data science experience
  • Seasoned in SAS programming (or R)
  • Experienced with CDISC (eg, STDM, ADaM) standards, and experienced with Clinical Pharmacology related datasets (eg, PC, adpc, adpp, and PPK / ER datasets)
  • Demonstrated ability to handle uncleaned data, identify data issues, and implement different programming procedures according to the pharmacometrics modelling needs
  • Excellent attention to fine data details
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