Job Summary
This hybrid role as a subject matter expert in biostatistics and statistical programming focuses on designing programming and validating clinical study analyses using SAS and Base SAS. The professional will support global teams by transforming complex clinical and observational data into reliable statistical outputs that drive regulatory submissions healthcare decisions and innovative therapies ensuring high quality and compliance in every deliverable.
Responsibilities
Transform complex clinical trial and observational datasets into well structured analysis datasets using SAS and Base SAS to enable robust statistical evaluation of study outcomes.Develop maintain and optimize reusable SAS programs and macros that streamline recurring statistical programming tasks and improve efficiency across multiple clinical projects.Create accurate tables listings and figures from clinical data using SAS procedures and data step programming to support study reports and regulatory documentation.Validate programming outputs through independent code review and rigorous comparison against specifications to ensure consistency traceability and regulatory grade quality.Collaborate closely with biostatistics and data management teams to interpret statistical analysis plans and translate them into detailed programming specifications and execution steps.Apply biostatistical principles to implement standard and advanced analyses that address efficacy safety and exploratory endpoints in clinical and post marketing studies.Conduct thorough discrepancy investigation and data driven issue resolution for programmed outputs by analyzing logs datasets and results to maintain data integrity.Document all programming activities including dataset derivations logic decisions and validation evidence in a clear and audit ready manner aligned with company and regulatory standards.Contribute to continuous process improvement by proposing refinements to programming workflows standard code libraries and quality control practices that enhance delivery speed and reliability.Support cross functional reviews by explaining statistical programming approaches and findings in a concise and accessible way that enables informed decision making by study stakeholders.Ensure alignment of programming deliverables with global compliance expectations for clinical research including adherence to internal policies and recognized biostatistical programming conventions.Participate in hybrid meetings and knowledge sharing sessions to exchange best practices in SAS programming and biostatistics fostering a collaborative and learning oriented environment.Advance the company mission to improve patient outcomes by delivering statistical evidence that supports safe effective and innovative medical solutions used in healthcare systems worldwide.Qualifications
Demonstrate solid hands on proficiency in SAS and Base SAS including data manipulation reporting and macro usage gained through two to four years of dedicated statistical programming experience.Apply strong knowledge of statistical programming concepts such as dataset derivation analysis data structures and standardization to build reliable and reproducible outputs.Utilize practical understanding of biostatistics including common clinical trial endpoints and statistical methods to implement analyses that are scientifically sound and contextually appropriate.Show capability to read write and speak English at a novice native level sufficient to understand requirements prepare documentation and participate in basic project discussions.Display familiarity with clinical research environments or healthcare data contexts where statistical programming and biostatistical reasoning are used to support study conclusions and decision making.Exhibit careful attention to detail problem solving mindset and time management skills that support accurate programming timely delivery and effective collaboration in a hybrid work model.Certifications Required
SAS Certified Specialist Base Programming or equivalent statistical programming certification relevant to SAS and biostatistics.
