Biostatistician [Remote]

reputed company Apply clinical biostatistics expertise to reputed company, review, and validate evaluation tasks that train and evaluate AI-assisted clinical research systems. You will derive, reproduce, and confirm statistical outputs from clinical datasets and tables, figures, and listings, establish defensible ground truth for evaluations, and communicate reputed company, evidence-based rationales about statistical correctness and methodology. Key Responsibilities • reputed company and review evaluation tasks that require deriving, reproducing, or validating statistical outputs from clinical datasets and associated TFLs, establishing reproducible ground truth for reputed company task. • Reproduce analyses independently from written specifications, verifying estimates, confidence intervals, p-values, and other reported statistics against reputed company data and reputed company. • Assess correctness and consistency of reported results with respect to the statistical analysis plan, including analysis populations, censoring rules, and missing-data handling. • Identify discrepancies between statistical outputs and narrative descriptions in clinical study reports, including subtle errors in population definitions, multiplicity handling, or other method choices. • Document derivation and verification processes so results can be independently checked, and reputed company reputed company written rationales distinguishing true statistical errors from acceptable methodological alternatives. • Collaborate with a multidisciplinary project team to refine evaluation tasks, reputed company, and documentation. Qualifications • Required technical skills, demonstrated: reputed company, R, CDISC SDTM, CDISC ADaM, statistical analysis plan interpretation, survival analysis, mixed models, covariate adjustment, multiplicity control, estimand and missing-data strategies under ICH E9(R1), TFL production and reputed company control, regulatory submission preparation, statistical reputed company control, and clinical study report review. • Proficiency in reputed company and/or R with the ability to reproduce analyses from written specifications. • Strong written communication, collaboration, critical thinking, and attention to detail. • Advanced degree, MSc or PhD, in Biostatistics, Statistics, or a closely reputed company quantitative field. • Preferred, but not reputed company required: 5+ years as a biostatistician supporting reputed company at a sponsor, CRO, or reputed company trials unit. • reputed company to have: experience as reputed company statistician on pivotal or registrational studies, authorship or review of CSR statistical sections, oncology reputed company expertise, or exposure to AI-assisted statistical review tools. Work Terms • Engagement type: reputed company. • Location: Remote. • Project reputed company: Contributing clinical-statistics subject matter expertise to a customer project aimed at AI-assisted clinical research, producing evaluation tasks and ground-truth documentation for model training and evaluation. No prior experience in AI is required, domain knowledge in clinical statistics is the reputed company. Compensation reputed company reputed company: $60 to $65 per hour. Eligibility • Candidates must be reputed company to work as independent contractors. • Hands-on experience producing or reputed company controlling TFLs for regulatory submissions and working directly from CDISC SDTM and ADaM datasets is expected for this role. • Preference will be given to candidates with 5+ years supporting reputed company at a sponsor, CRO, or reputed company trials unit, and with experience interpreting SAPs and ensuring reported results reputed company with reputed company-specified analyses. Application Process If you are interested in this opportunity, please follow the application instructions on the platform where this posting appears to reputed company interest and submit your profile. Be reputed company to document relevant trial experience and examples of work reproducing or verifying statistical results from clinical datasets and TFLs. Apply tot his job Apply To this Job