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This is a fully remote position, open to candidates based in Italy.

Pay: $60–$65/hr

Role Type: Contractor

Location: Remote

We are 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

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- 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

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- 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. xlwpduy

- 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.

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