Lead Statistical Programmer - Global Studies (Remote) Job at RemoteWorker US, Fairfield, CT

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  • RemoteWorker US
  • Fairfield, CT

Job Description

Contact: Neisha Camacho/Terra Parsons - teamnt@penfieldsearch.com
No 3rd party candidates

We are seeking a highly experienced Statistical Programmer to lead programming activities across global clinical studies. This role operates beyond executional programming, with responsibility for oversight of CRO deliverables, validation of outputs, and end-to-end accountability for statistical programming packages.

Key Responsibilities

  • Lead statistical programming activities across global studies (EU and China exposure preferred)

  • Serve as primary programming lead in collaboration with Biostatistics

  • Develop, review, and validate SDTM and ADaM datasets in accordance with CDISC standards

  • Review specifications and proactively challenge inconsistencies in protocols, SAPs, and dataset definitions

  • Validate program outputs and ensure accuracy, quality, and regulatory compliance

  • Provide oversight and guidance to CRO partners, consolidating and communicating feedback effectively

  • Manage timelines, delivery packages, and milestone commitments

  • Contribute to continuous improvement of programming processes and standards

Core Requirements

  • Strong expertise in CDISC standards, including ADaM and SDTM

  • Demonstrated experience reviewing specs and ensuring high-quality, submission-ready deliverables
  • Working experience in LSAF environment
  • Experience validating CRO programming deliverables
  • Ability to operate with increased performance accountability and ownership
  • Strong CRO-facing communication and collaboration skills
  • Proven ability to manage multiple global studies simultaneously

Qualifications

  • Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, or related field

  • 5+ years of SAS programming experience within pharmaceutical/biotech
  • Strong understanding of statistical methods used in clinical trial analysis
  • Knowledge of Good Programming Practices and GCP

Preferred

  • Experience with R programming

Additional Requirements

  • Hands-on experience with LSAF - Life Sciences Analytical Framework

  • Practical experience with multiple imputation (MI), particularly under Missing at Random (MAR) assumptions
  • Familiarity with the estimands framework (ICH E9 R1) and managing intercurrent events (ICEs) within ADaM domains using various strategies

Job Tags

Contract work, Work experience placement, Remote work

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