Scientific Data Analyst for Classification‑Framework Validation (Peer‑Reviewed Experience Required)

Overview We are conducting a scientific validation study involving phenotype‑classification and measurement‑science analysis. This project requires research‑grade statistical modeling, publication‑quality figures, and peer‑reviewed scientific writing. This is not a business analytics or dashboard project. Required Expertise * Peer‑reviewed scientific publications * Statistical inference (regression, clustering, diagnostics, effect sizes) * Classification‑framework validation * Measurement‑science literacy (proxy metrics, construct validity) * Publication‑grade visualization (multi‑panel figures, scientific formatting) * Scientific writing (methods, results, figure captions, bibliography) * Python or R for research workflows Preferred Background * Computational biology * Epidemiology * Psychology research * Biomedical data analysis * Digital phenotyping * Human‑subject data analysis Project Tasks * Validate a phenotype‑classification framework * Perform regression and clustering analyses * Produce publication‑grade figures * Write Methods and Results sections * Interpret effect sizes and structured inference * Prepare reproducible scientific pipelines Screening Test Required Applicants must complete a short scientific analysis task (regression + diagnostics + figure + Methods/Results). Deliverables * Statistical analysis * Scientific figures * Methods section * Results section * Interpretation of classification validity To Apply Submit: * A link to a peer‑reviewed paper you contributed to * A link to a scientific figure you produced * A short description of your experience with measurement‑science or classification frameworks