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Sr.Statistical Programmer

Katalyst Healthcares & Life Sciences -
Boulder, CO

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Job Details

Contract

Qualifications

FDA submissions
SAS
SAS language
SQL
Bachelor's degree
Industry trends
CDISC standards
Regulatory submission editing and review
Communication with regulatory authorities for clinical trials
Cross-functional collaboration
Cross-functional communication
Data analysis software

Full Job Description

Job Description:

We are seeking a highly motivated and qualified individual to join our Clinical Department as a Senior Statistical Programmer and work as part of a team to drive success.
Ideal candidates will be self-motivated, independent, committed to the generation of high-quality data within a fast-paced and innovative research team.
The Senior Statistical Programmer will serve as the lead statistical programmer and is responsible for statistical programming activities such as designing, developing, validating, updating, and documenting SAS programs to generate analysis datasets, data listings, summary tables, and statistical graphs supporting statistical analyses.
This position requires close collaboration with cross-functional teams to ensure the integrity and accuracy of clinical data used in regulatory filings and internal reporting.

Responsibilities:

Independently develop, validate, document and troubleshoot SAS programs for the preparation of periodic internal reports, regulatory submissions, and ad hoc analyses.
Create and maintain analysis and submission datasets (ADaM, SDTM) in compliance with CDISC standards and regulatory guidance.
Design, develop, validate, update, and document SAS programs to generate analysis datasets, data listings, tables, and graphs of high quality in a timely manner.
Support submission activities including preparation of data packages, eCTD deliverables, and responses to regulatory agencies,
Communicate with team members about statistical programming related to trial timelines, data quality, and results interpretation.
Develop software tools, SAS macros and utilities to automate programming activities and improve programming efficiency and quality.
Create SAS macros or other tools to enhance the efficient delivery of statistical services, providing associated documentation and staff training as needed.
Program quality checks for clinical study raw data and report findings.
Review or author SDTM and ADaM specifications and datasets.
Manage CROs, including reviewing or validating statistical deliverables of vendors.
Provides input in the design and development of case report forms.
Contribute to the preparation of research reports and presentations for internal project teams, leadership team, and external audience.
Establish and maintain excellent working relationships with critical collaborative partners throughout the company.

Requirements:

Bachelor's degree in Biostatistics, Mathematics, Statistics, Computer Science, or related field
Minimum 6 years' experience in bio-pharma statistical programming
Advanced SAS programming skills in SAS/Base, SAS/Macro, SAS/STAT, SAS/Graph, and SAS/SQL with a demonstrated mastery of SAS/STAT procedures
Strong expertise in CDISC including SDTM, ADaM, and CDASH
Extensive experience in SAS macro functions and dynamic code generations.
Experience in regulatory submissions (e.g., NDAs and DSURs)
High attention to detail, with a focus on quality and traceability in all deliverables
Strong interpersonal and teamwork skills with a collaborative mindset and the ability to manage multiple priorities in a fast-paced and dynamic environment with shifting timelines and evolving needs
Take initiatives to solve problems proactively and think critically
Willing to adapt to changing business needs, able to pivot between tasks
Able to make complex programming and data-related decisions independently
Comprehensive knowledge and deep understanding of statistical programming environments, processes, procedures, and roles for clinical development from Phase 1 through regulatory submission
Up to date with CDISC standards, industry trends, best practices, and statistical programming methodology

Quick Apply

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