[Hiring] Biostatistician @24-MAG

Role Description

We are sharing a specialised consulting opportunity for experienced Biostatisticians with strong expertise in clinical-trial statistics, SAS and R, CDISC SDTM/ADaM, Statistical Analysis Plan interpretation, TFL production and quality control, survival analysis, mixed models, estimands, and regulatory statistical review to contribute to an advanced AI training and clinical-research evaluation project. Selected professionals will reproduce and validate clinical-trial analyses, assess consistency with Statistical Analysis Plans, review TFLs and Clinical Study Reports, and establish defensible statistical ground truth for evaluation tasks. No prior experience in AI is required.

Qualifications

• 5+ years of experience as a biostatistician supporting clinical trials
• Experience at a sponsor, CRO, academic trials unit, or comparable clinical-research organisation
• Hands-on experience producing or quality controlling TFLs for regulatory submissions
• Direct experience with CDISC SDTM and ADaM datasets
• Strong proficiency in SAS and/or R
• Ability to independently reproduce statistical analyses from written specifications
• Strong knowledge of confirmatory trial methodology, survival analysis, and mixed models
• Familiarity with covariate adjustment, multiplicity control, estimands, and missing-data strategies under ICH E9(R1)
• Demonstrated experience interpreting Statistical Analysis Plans
• CSR or regulatory statistical-review experience is highly valuable
• MSc or PhD in Biostatistics, Statistics, or a closely related quantitative discipline
• Lead-statistician experience on pivotal or registrational studies is advantageous
• Oncology endpoint expertise is beneficial
• No prior AI-training or model-evaluation experience is required

Requirements

• Independent contractor engagement
• Fully remote
• Compensation: $60–$65/hour
• Work will involve clinical-trial statistical analysis, CDISC SDTM/ADaM review, SAP interpretation, TFL validation, statistical quality control, CSR review, and regulatory statistical evaluation
• Assignments may involve clinical datasets, TFLs, SAPs, CSRs, analysis specifications, and structured statistical-evaluation tasks
• Work may require independently reproducing analyses and documenting derivations for verification
• Project scope, workload, therapeutic areas, datasets, and evaluation standards may evolve depending on project requirements
• Work must be completed without using confidential, proprietary, or identifiable patient information belonging to any employer, sponsor, CRO, healthcare organisation, research institution, patient, or other third party