Clinical Analyst Intern (Dozee)

6/2/20261 min read

Roles and Responsibilities

Real World Evidence & Data Analysis

  • Analyse de-identified patient monitoring data from hospital deployments to generate Real World Evidence on clinical outcomes, early warning performance, and care-pathway impact.

  • Run descriptive and inferential statistical analyses (cohort comparisons, sensitivity / specificity, length-of-stay analyses, time-to-event) using SQL, Python, R, or SPSS.

  • Support hypothesis-driven studies in collaboration with clinical leads, contributing to study design, cohort definition, and outcome measurement.

Clinical Research & Literature

  • Conduct structured medical literature reviews on PubMed and equivalent databases to
    benchmark Dozee's clinical findings against the published evidence base.

  • Summarise study protocols, peer-reviewed papers, and clinical guidelines into clear, decision-
    ready briefs for the Medical Affairs team.

  • Support preparation of manuscripts, abstracts, and conference posters with clean data tables,
    figures, and citation management.

Documentation & Reporting

  • Create and maintain structured documentation including study protocols, statistical analysis plans, data dictionaries, and final study reports.

  • Document data sources, cohort selection logic, exclusion criteria, and analytical assumptions to
    ensure reproducibility.

  • Build and maintain dashboards that track ongoing clinical KPIs and study-level metrics for
    internal review.

Experience

  • Currently pursuing or recently completed a degree in Life Sciences, Biostatistics, Public Health,Pharmacy, Biomedical Engineering, or a related discipline. A clinical background (MBBS /BDS / Nursing) is a strong plus.

  • Working knowledge of SQL and Python for data extraction, cleaning, and analysis.

  • Familiarity with at least one statistical tool such as R or SPSS for hypothesis testing, regression, and survival analysis.

  • Comfortable conducting medical literature reviews on PubMed and synthesising findings into structured summaries.

  • Strong analytical mindset with proficiency in Excel / Google Sheets.

  • Excellent written communication skills with the ability to produce clear, concise scientific documentation.

  • Strong attention to detail, organisational skills, and the ability to manage multiple work streams simultaneously.

  • A collaborative attitude with the ability to work effectively in a cross-functional team spanning
    clinical, data, and product functions.

  • Genuine curiosity about clinical research, patient outcomes, and the role of AI in healthcare.

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