About the role
Role Title: Biostatistician
Role Type: Contractor
Location: Remote
micro1 is engaging Biostatisticians to contribute their clinical statistics expertise to a dynamic customer project focused on AI-assisted clinical research. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Scope of Work
Author and review evaluation tasks that require deriving, reproducing, or validating statistical outputs from clinical datasets and associated tables, figures, and listings (TFLs).
Apply expert judgment to assess the correctness and consistency of reported estimates, confidence intervals, p-values, analysis populations, and missing data handling in alignment with the statistical analysis plan (SAP).
Identify discrepancies between statistical outputs and their narrative descriptions in clinical study reports (CSR), including subtle errors in population definitions, censoring rules, or multiplicity handling.
Establish defensible ground truth for each evaluation task, documenting the derivation process to enable independent verification.
Provide structured written rationales distinguishing true statistical errors from acceptable methodological alternatives, employing clear and concise communication.
Collaborate with a multidisciplinary project team, providing statistical insights and feedback as needed to refine evaluation tasks and criteria.
Preferred Qualifications
5+ years as a biostatistician supporting clinical trials at a sponsor, CRO, or academic trials unit.
Hands-on experience producing or quality controlling TFLs for regulatory submissions and working directly from CDISC SDTM/ADaM datasets.
Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies under ICH E9(R1).
Proficiency in SAS and/or R, with the ability to independently reproduce analyses from written specifications.
Ability to interpret SAPs and ensure reported results are consistent with pre-specified analyses.
Advanced degree (MSc or PhD) in Biostatistics, Statistics, or a closely related quantitative field.
Nice to have: Experience as lead statistician on pivotal/registrational studies, authoring or reviewing CSR statistical sections, oncology endpoint expertise, and exposure to AI-assisted statistical review tools.
Originally posted on Himalayas