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Clinical SAS Programmer

2 months ago

South Plainfield, United States Katalyst Healthcares & Life Sciences Full time
Responsibilities:

Works collaboratively with Clinical Development staff to meet project deliverables and timelines for statistical data analysis and reporting.

Assesses the quality and consistency of analysis data and performs cross–study analyses.

Uses internal macros or writes SAS macros to automate study deliverables.

Works as a primary programmer for multiple Phase 1–4 studies.

Assists in submissions of electronic data (e.g., SAS data sets) to regulatory agencies.

Independently develops analysis specification & programs.

Identifies potential issues in study documentation and proposes solutions.

Contributes to strategic initiatives.

Assist with study and systems audits by GSI Compliance Group and external bodies and respond to audit questions and findings.

Promote and communicate awareness of programming and the role of the Biometrics department (internal/external; scientific/process)

Excellent verbal and written communication skills and interpersonal skills are required.

Has thorough knowledge of clinical trial study design and electronic data submission requirements. Must be able to work independently on multiple concurrent projects.

Requirements:

Programming standardization activities and departmental initiatives.

Collaborate cross–functionally with Macro team and CDMA as needed.

Successfully interacts within Clinical Data Science, with Clinical Development and Regulatory Affairs groups on a frequent basis.

Expert knowledge of Adam data standards and FDA/PMDA/EMA submission requirements required.

Develop, update, and maintain Adam standards.

Review and align current Adam Client CORE standards to Regulatory Agency requirements, CDISC TAUGS, and CDISC standards.

Review SDTM standards for updates and impacts on current Adam CORE standards.

Participate in study specific Adam submission package reviews across multiple authorities.

Statistical programmers work collaboratively with internal colleagues and external vendors to ensure the efficient, high–quality production of analysis datasets and statistical outputs for study reports and integrated