Manager, Statistical Programming

Rezolute is a late-stage rare disease biopharmaceutical company focused on developing transformative therapies for patients living with severe metabolic and endocrine disorders. Our mission is to bring hope and meaningful solutions to patients and families affected by rare and difficult-to-treat diseases through scientific innovation, collaboration, and integrity.

Rezolute’s lead investigational therapy, RZ358 (ersodetug), is a fully human monoclonal antibody in late-stage clinical development for the treatment of hypoglycemia due to congenital and acquired forms of hyperinsulinism (HI). As Rezolute expands its medical and scientific focus into tumor-related hyperinsulinism (tumor HI), most commonly related to pancreatic neuroendocrine tumors (insulinomas) or paraneoplastic hypoglycemia (NICTH), the company is committed to advancing novel therapeutic strategies that address this rare and complex form of hypoglycemia associated with insulin-secreting tumors and related neuro-oncology disorders

More information can be found at rezolutebio.com

Position Summary

The Manager of Statistical Programming is responsible for delivering study-level programming deliverables and milestones. The role combines hands-on programming in SAS and R with oversight of a small team or of CRO programmers assigned to a study.

The position requires working knowledge of statistical programming languages and software, clinical trial data, and the drug development process. The incumbent develops and oversees programs that generate CDISC-compliant SDTM and ADaM datasets, TLFs, and reports supporting the review of clinical data. The incumbent also writes validation programs and general-purpose code, prepares documentation to support electronic submissions, and contributes to programming standards and templates.

Responsibilities:

• Plans and delivers statistical programming for assigned studies in support of clinical trials, regulatory submissions, publications, and ad hoc analysis requests, following applicable regulatory guidelines and standards.
• Tracks programming timelines for assigned studies and flags risks to the Director so deliverables stay aligned with the study schedule.
• Creates or oversees the creation of CDISC-compliant SDTM and ADaM datasets, and performs conformance checks (e.g., Pinnacle 21) before delivery.
• Develops and validates TLFs and analysis datasets using SAS and R; performs independent QC of programming produced by others, including cross-language validation where appropriate.
• Assigns and reviews the work of a small team of internal programmers and/or CRO programmers; provides day-to-day direction, feedback, and mentoring.
• Reviews CRO deliverables, specifications, and documentation for quality and standards compliance, and escalates issues as needed.
• Participates in study meetings with Clinical Operations, Data Management, Safety, and Biostatistics to develop specifications and reports.
• Writes and maintains batch scripts to schedule SAS and R jobs and distribute reports to the clinical team.
• Prepares programming documentation supporting electronic submissions, including define.xml inputs and reviewer guide content.
• Contributes to the development of SAS macros, R functions, standards, templates, and SOPs, and to cross-functional initiatives.
• Provides input on programming tools and infrastructure needs, including SAS and R environments, and works with IT as needed.

Qualifications:

• BS/BA in Statistics, Computer Science, Mathematics, Life Sciences, or a related field; MS preferred.
• 8+ years of statistical programming experience in pharma, biotech, or CRO with a BS, or 6+ years with an MS.
• 1–2 years of experience supervising programmers or serving as lead programmer on a study.
• Strong SAS skills (Base, Macro, SQL, STAT, ODS/Graph).
• Working proficiency in R for clinical data manipulation, analysis, and reporting (e.g., tidyverse, admiral, gt, rtables, or similar).
• Experience developing R Shiny applications for interactive data review, safety monitoring, or visualization of clinical trial data is a plus.
• Working knowledge of CDISC SDTM and ADaM, controlled terminology, and Define-XML.
• Familiarity with ICH guidelines and GCP; exposure to a regulatory submission is a plus.
• Experience with Python for automation, data processing, or tooling is a plus.
• Clear written and verbal communication; comfortable working directly with statisticians and clinical teams.