Evidence synthesis assistant

Company Description At GS Analytics, we specialise in advanced evidence synthesis and in-silico clinical analytics, transforming complex clinical data into meaningful scientific insights through rigorous computational methodologies. By leveraging sophisticated statistical modelling and data-driven research frameworks, we deliver high-impact systematic reviews and regulatory-grade outputs for global academic and healthcare stakeholders. Our culture is rooted in intellectual excellence, innovation, and continuous professional growth, empowering our team to work at the forefront of computational science and evidence-based healthcare, shaping research that drives real-world clinical advancement.

Role Description We are seeking a highly motivated Research Analyst – Evidence Synthesis to join our scientific team at GS Analytics. The role involves comprehensive biomedical literature review, structured data extraction, and execution of systematic reviews, meta-analyses, and network meta-analyses using robust methodological frameworks (PRISMA, CONSORT). The candidate will be responsible for statistical analysis using appropriate software, interpretation of pooled outcomes, preparation of forest plots, risk-of-bias assessment, and manuscript drafting for peer-reviewed publication. Exposure to bibliometric analysis, scientometric mapping, and research trend evaluation is expected. A foundational understanding of pharmacokinetics (PK), pharmacodynamics (PD), and drug-response relationships is essential, particularly in translating clinical and in-silico findings into meaningful therapeutic insights. The role demands analytical rigor, scientific writing excellence, and the ability to synthesize complex clinical data into high-impact, publication-ready outputs within regulatory and academic standards. Essential Qualifications Master’s degree (or higher) in Pharmacy, Clinical Research, Pharmacology, Public Health, Biotechnology, Life Sciences or Bachelor's in Medicine/Dental sciences or equivalent degree. Demonstrated experience in conducting systematic reviews, meta-analyses via eminent publications. Proficiency in biomedical literature databases (PubMed, Scopus, Web of Science, Embase). Experience in structured data extraction, risk-of-bias assessment, and adherence to PRISMA guidelines. Familiarity with statistical software (RevMan, R, STATA, CMA, or SAS). Experience in manuscript writing for peer-reviewed journals. Understanding of bibliometric/scientometric analysis is desirable. Strong analytical reasoning, scientific writing skills, and attention to methodological detail. Ability to work independently in a research-driven, deadline-oriented environment.