Clinical Research AI Evaluation Specialist

About OpenTrain

OpenTrain is the #1 platform for people who build careers in AI training and data labeling. We help freelancers discover specialized projects, consolidate proof of work, and grow a durable portfolio of AI‑training experience.

This role is hired and managed by OpenTrain AI. We support flexible, remote contractor work so contributors can apply domain expertise to the systems that shape modern AI.

About AI training work in clinical research

AI training (data labeling/annotation) is the human side of building AI: experts evaluate model outputs, write model answers, and rate reasoning quality so models learn to be accurate and safe.

Clinical research evaluation is a high‑impact subfield: your assessments help ensure models interpret trial data, evidence, and medical claims correctly and responsibly.

The role

You will evaluate AI‑generated clinical research and biomedical text for correctness, clarity, rigor, and safety; identify methodological and statistical issues; and produce clear, evidence‑based gold standard answers and explanations.

Work focuses on text data and includes evaluation ratings, text generation (model answers), and RLHF‑style feedback.

• Position type: remote contractor, part‑time (20+ hours/week)
• Primary data type: text; labeling tasks include EVALUATION_RATING, TEXT_GENERATION, and RLHF

What you'll do

• Review AI‑generated clinical research and biomedical content for accuracy, clarity, and adherence to prompts
• Identify problems in study design, endpoint selection, bias, confounding, randomization, and blinding
• Evaluate statistical reasoning: effect sizes, confidence intervals, p‑values, multiple comparisons, missing data, and sensitivity analyses
• Fact‑check medical and scientific claims against primary literature and strong research standards
• Compare and rate multiple AI responses for correctness, rigor, safety, and usefulness
• Write high‑quality model answers and expert explanations that demonstrate sound research reasoning
• Flag outputs that could lead to misleading interpretations or unsafe clinical recommendations

Requirements

• Bachelor's degree or higher in Public Health, Epidemiology, Biostatistics, Clinical Research, Biomedical Sciences, PharmD, MD, DO, RN, or a related field
• 5+ years of professional clinical research experience
• Strong command of study design, endpoints, inclusion/exclusion criteria, power/sample size intuition, and result interpretation
• Comfortable with effect sizes, confidence intervals, p‑values, multiple comparisons, missing data, and sensitivity analyses
• Deep understanding of bias, confounding, and causality in clinical research
• Familiarity with clinical trial operations concepts and Good Clinical Practice (GCP) principles
• Strong scientific writing and minimum C1 English proficiency
• Proven ability to work reliably as a self‑directed contractor across time zones

Helpful background

• Experience with literature reviews, evidence‑based medicine, and clinical trial design
• Prior experience in AI data training, annotation, editorial QA, systematic reviews, or guideline development is strongly preferred
• Previous work producing written explanations, model answers, or evaluation rubrics for scientific content

Work arrangement & compensation

This is a short‑term, hourly remote contractor role with flexible collaboration across time zones. Expect to work 20+ hours per week.

Hourly pay: USD $40–$70 per hour (project pays hourly; top rate $70/hr). This is contractor pay and may vary by experience and task complexity.

• Required language: English (C1 or higher)
• Eligible countries: VN, TL, TH, SG, PK, PH, NP, MY, LK, KH, ID, BT, BD, IN, BR, DE, US

How to apply and what we look for

Apply through your OpenTrain account with a CV that highlights clinical research experience and examples of scientific writing or evaluation work. Include any relevant AI evaluation or systematic review experience.

We look for demonstrable clinical research expertise, strong statistical intuition, careful written communication, and prior contractor reliability. Clear examples of past work evaluating trials or producing research syntheses are highly valued.