Statistical Programmer Health Science/Pharma

As a Statistical Programmer in our clinical research team, you will have the crucial responsibility of programming, validating, and delivering statistical outputs for clinical trials. Your role will involve ensuring compliance with regulatory standards and industry best practices. Key Responsibilities: - Develop and maintain SAS programs for clinical trial data processing, analysis, and reporting - Map clinical trial data to CDISC standards (SDTM and ADaM) to ensure regulatory compliance - Create and maintain analysis datasets following CDISC implementation guidelines - Perform data validation and quality control checks to uphold data integrity - Generate and maintain CDISC documentation including define.xml files, reviewer's guides, and annotated case report forms (aCRF) - Conduct Pinnacle21 validation checks, resolve compliance issues, and ensure all deliverables meet regulatory submission standards - Maintain comprehensive programming documentation and version control - Produce Tables, Listings, and Figures (TLFs) based on Statistical Analysis Plans (SAP) and collaborate with biostatisticians for complex statistical analyses - Support clinical study reports, regulatory submissions, and perform ad-hoc analyses as requested by clinical teams - Work closely with clinical data management, biostatistics, and regulatory affairs teams, participate in project meetings, provide technical expertise, support timeline planning, and deliverable tracking - Mentor junior programmers and provide technical guidance Qualification Required: - Minimum of 3+ years of experience as a statistical programmer in clinical research or the pharmaceutical industry - Advanced SAS programming skills including Base SAS, SAS/STAT, SAS/GRAPH, and SAS Macro language - Strong understanding of clinical trials, CDISC standards, and experience with CDISC documentation - Soft skills such as excellent communication, problem-solving mentality, attention to detail, and effective team collaboration - Preferred qualifications include experience with Real-World Data (RWD), Pharmacokinetic (PK) calculations, R programming, and knowledge of other statistical software packages - Bachelor's degree in Statistics, Mathematics, Computer Science, Life Sciences, or a related field is required; an advanced degree is preferred but not mandatory with relevant experience Join our team and contribute meaningfully to clinical research, while developing expertise in regulatory compliance and industry best practices.,