Clinical Analyst Intern

• We are looking for a curious and detail-oriented Clinical Analyst Intern to join our Clinical / Medical
• Affairs team. In this role, you will work closely with clinicians, data scientists, and medical affairs
• leads to generate Real World Evidence (RWE) from Dozee's deployments across hospitals, helping
• shape clinical decisions, scientific publications, and product direction through rigorous data
• analysis and structured documentation.

Roles and Responsibilites

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.