Biostatistician

RemoteJobsOne; Singapore; Remote; SGD 106,000 - 114,000; Full time

Job summary

RemoteJobsOne is seeking a Biostatistician for a fully remote, contract-based role open to candidates based in Singapore. You will contribute statistical expertise to AI-assisted clinical research efforts, focusing on training data quality and evaluation of statistical outputs.

Ideal candidates have 5+ years in biostatistics for clinical trials, SAS/R proficiency, and experience with CDISC SDTM/ADaM. Advanced degree preferred; strong communication and collaboration skills are essential.

Qualifications

• 5+ years of biostatistics experience in clinical trials.
• Experience producing or QCing TFLs for regulatory submissions.
• Familiarity with CDISC SDTM/ADaM datasets and ICH E9(R1) concepts.
• Proficiency in SAS and/or R; able to reproduce analyses from specs.
• Advanced degree in Biostatistics or related field.

Responsibilities

• Author and review statistical outputs from clinical datasets and TFLs.
• Assess correctness of estimates, CIs, p-values, and analyses populations.
• Check CSR narratives for consistent population definitions and censoring rules.
• Document derivation processes to enable independent verification.
• Provide written rationales distinguishing true errors from alternatives.
• Collaborate with project team to refine evaluation tasks and criteria.

Skills

Biostatistics

Clinical trials

Statistical methods

SAS

R

SAP interpretation

Education

MSc or PhD in Biostatistics

Tools

SDTM/ADaM datasets

Job description

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

Pay: $60–$65/hr

Role Title: Biostatistician

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

1. Author and review evaluation tasks that require deriving, reproducing, or validating statistical outputs from clinical datasets and associated tables, figures, and listings (TFLs).
2. 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).
3. 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.
4. Establish defensible ground truth for each evaluation task, documenting the derivation process to enable independent verification.
5. Provide structured written rationales distinguishing true statistical errors from acceptable methodological alternatives, employing clear and concise communication.
6. Collaborate with a multidisciplinary project team, providing statistical insights and feedback as needed to refine evaluation tasks and criteria.

Preferred Qualifications

1. 5+ years as a biostatistician supporting clinical trials at a sponsor, CRO, or academic trials unit.
2. Hands-on experience producing or quality controlling TFLs for regulatory submissions and working directly from CDISC SDTM/ADaM datasets.
3. 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).
4. Proficiency in SAS and/or R, with the ability to independently reproduce analyses from written specifications.
5. Ability to interpret SAPs and ensure reported results are consistent with pre-specified analyses.
6. Advanced degree (MSc or PhD) in Biostatistics, Statistics, or a closely related quantitative field.
7. 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.