Statistical Programmer II

About the role

The Statistical Programming team at LivaNova develops datasets from clinical trials and delivers tables, listings, and figures (TLFs) per Statistical Analysis Plans (SAPs) to support new products and therapies, as well as to generate evidence for marketed devices. This team also supports additional programming activities for clinical operations and other areas of the company, including R&D and Quality.

Responsibilities

• Support programming activities for multiple projects on clinical study reports and publications.
• Accountable for clinical statistical programming deliverables and for ensuring excellence in programming activities in terms of quality and timelines for clinical trials under the responsibility of Statistics & Data Management.
• Collaborate with Statistics, Data Management, Clinical, and vendor teams to clarify requirements and resolve data or programming issues.
• Develop, validate, and maintain SAS programs in accordance with study requirements, internal standards, and SOPs.
• Contribute to the creation, validation, and documentation of SDTM and ADaM datasets.
• Responsible for producing programming outputs, validation, and related documentation to ensure accuracy, consistency, and traceability.
• Ensure deliverables meet expectations in terms of timelines and quality, regulatory and key user group requirements (e.g., CDISC), operational efficiency, and alignment with the study's clinical and statistical objectives.
• Provide input into SAP, analysis specifications, and data presentations for clinical trials.
• Support ongoing workflow modernization, migration activities, and standardization initiatives.
• Participate in process improvement activities related to programming efficiency, quality, and standardization.

Requirements

• Bachelor’s degree or higher in statistics, mathematics, computer science, life sciences, data science, or related field.
• Relevant experience in clinical trial programming, clinical data analysis, statistical programming, or regulated data environments.
• Strong SAS programming skills, including data step, procedures, macros, and debugging.
• Ability to write clear, validated, reusable, and well-documented code.
• Understanding of programming quality control, validation, and traceability expectations.
• Working knowledge of CDISC standards, especially SDTM and ADaM.
• Experience with R, Python, SQL, Git, or other modern programming/version control tools.
• Experience with SAS Enterprise Guide or other SAS-based clinical programming environments.
• Familiarity with data visualization, dashboards, automation, or workflow improvement.
• Experience working with vendors or cross-functional global teams.
• Understanding of controlled programming environments, SOPs, and audit-ready documentation.

Qualifications

• Strong attention to detail and quality.
• Ability to work independently on assigned tasks with appropriate guidance.
• Good communication skills and ability to collaborate with Statistics, Data Management, Clinical, and external vendors.

Skills

• SAS programming skills.
• CDISC standards, especially SDTM and ADaM.
• Data visualization, dashboards, automation, or workflow improvement.
• Experience working with vendors or cross-functional global teams.
• Understanding of controlled programming environments, SOPs, and audit-ready documentation.

Benefits

Pay transparency: A reasonable estimate of the annual base salary for this position is $90,000 - $100,000 plus discretionary annual bonus. Pay ranges may vary by location and are awarded based on experience.

• Health benefits – Medical, Dental, Vision
• Personal and Vacation Time
• Retail and Savings Plan (401K)
• Employee Stock Purchase Plan
• Training & Education Assistance
• Bonus Referral Program
• Service Awards
• Employee Recognition Program
• Flexible Work Schedules

Company Culture

LivaNova values equality and diversity. We are committed to ensuring that our recruitment process is fair, transparent and free from unlawful discrimination. Our selection process is driven by the key demands/requirements for the role rather than bias or discrimination on the basis of a candidate’s sex, gender identity, age, marital status, veteran status, non-job-related disability/handicap or medical condition, family status, sexual orientation, religion, color, ethnicity, race or any other legally protected classification.