Note: The job is a remote job and is open to candidates in USA. Planet Pharma is seeking a skilled and detail-oriented Clinical Spotfire / SAS Programmer to support their clinical trial data management and statistical programming initiatives. In this role, you will develop validated SAS programs and high-impact Spotfire dashboards to ensure data quality and regulatory compliance.
Responsibilities
- Develop, validate, and execute SAS programs, macros, and SQL queries to generate data review listings, tables, profiles, figures, and standard datasets. Perform debugging, error resolution, and continuous code optimization
- Design, build, and deploy data visualization packages and interactive dashboards using TIBCO Spotfire per project specifications. Handle complex data wrangling within Spotfire to integrate diverse data streams
- Perform precise data mapping between disparate data sources and standard outputs utilizing industry best practices and annotated CRFs. Process, analyze, and execute data reconciliation requirements
- Generate comprehensive validation, quality check, and QC documentation to meet strict regulatory standards and internal guidelines. Identify, track, and resolve data quality and consistency issues
- Act as the accountable programming lead for assigned studies. Collaborate closely with Data Managers, Biostatisticians, and clinical study teams to facilitate specification development for complex reports
- Support routine user administration tasks within the Electronic Data Capture (EDC) system using established templates and protocols
Skills
- Proven experience developing clinical visual analytics and performing advanced data wrangling within TIBCO Spotfire is required
- Advanced, hands-on programming skills in SAS
- Strong familiarity with SAS macros and PROC SQL
- Solid general knowledge of clinical data standards and best practices, including CDISC, CDASH, and SDTM
- Demonstrated experience working within a pharmaceutical, biotechnology, or CRO environment supporting clinical trials
- Bachelor's degree or higher in a scientific, biological, statistical, computer science, or related quantitative discipline
- SAS Certification is highly preferred
- M.S. in Statistics, Mathematics, or Epidemiology is highly preferred
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