Senior Research Analyst – Life Sciences

Capestart Inc.; Nagercoil, Chennai District; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Capestart Inc. in Tamil Nadu seeks a Senior Life Science Research Analyst with 6–8 years of experience in SLR, TLR, MA and NMA to run literature reviews from protocol development through reporting across human, animal and mechanistic evidence streams.

You will manage multiple projects, mentor junior analysts, and help refine AI-assisted evidence synthesis workflows for pharmaceutical, biotechnology, medical device and public health clients, ensuring methodological rigor and on-time delivery.

Qualifications

• 6–8 years of experience in SLR, TLR, MA and NMA.
• Experience across human, animal and mechanistic evidence streams.
• Ability to manage multiple projects and mentor junior analysts.
• Experience with GRADE and PRISMA.

Responsibilities

• Independently run end-to-end SLRs and TLRs, including protocols, research questions, eligibility criteria, and search strategies across major biomedical databases.
• Lead title/abstract and full-text screening, data extraction and evidence synthesis with source-level traceability.
• Conduct and lead MA and NMA; interpret statistical outputs and translate into clear narratives.
• Synthesize human, animal and mechanistic evidence for exposure-outcome questions.
• Validate and QC AI-assisted screening and extraction; identify issues and suggest improvements.
• Perform risk of bias and quality assessments; apply GRADE where relevant.
• Prepare client-ready reports, manuscripts, evidence summaries and presentations with versioned drafts.
• Perform QC and peer review of team outputs; manage multiple projects and timelines.
• Mentor junior analysts and share best practices; keep up with AI-assisted review methods.

Skills

Systematic review

Meta-analysis

Network meta-analysis

Evidence synthesis

Data extraction

Bias assessment

GRADE

PRISMA

AI-assisted review

Project management

Mentoring

Job description

We are seeking a Senior Life Science Research Analyst with 6 to 8 years of experience in SLR, TLR, meta-analysis (MA) and network meta-analysis (NMA). You will independently run literature review projects from protocol development through reporting, across human, animal and mechanistic evidence streams, and keep them methodologically rigorous, scientifically accurate and on schedule. You will also manage several projects at once, mentor junior analysts, and help refine AI-assisted evidence synthesis workflows for pharmaceutical, biotechnology, medical device and public health clients.

Roles and Responsibilities

• Independently run end-to-end SLRs and TLRs, including protocols, research questions, eligibility criteria, and search strategies across major biomedical and occupational health databases, with repeat searches and comparison against reference sets.
• Lead title/abstract and full-text screening, data extraction and evidence synthesis, with source-level traceability.
• Conduct and lead MA and NMA. Interpret statistical outputs (relative risks, odds ratios, mean differences, heterogeneity) and turn them into clear scientific narratives.
• Synthesize and integrate human, animal and mechanistic evidence for exposure-outcome and hazard identification questions.
• Validate and QC AI-assisted screening and extraction, including table and figure parsing, by comparing outputs with human-reviewed results. Identify workflow or data-quality issues and recommend improvements.
• Conduct risk of bias and quality assessments with tools suited to each evidence stream, and apply GRADE where relevant.
• Apply PRISMA and accepted evidence synthesis methodology throughout.
• Prepare client-ready reports, manuscripts, evidence summaries and presentations, with versioned drafts and comment-response documentation. Ensure Word and PDF deliverables are accessible.
• Perform QC and peer review of team outputs.
• Manage multiple projects and timelines, and contribute to project planning, status reporting and client discussions.
• Mentor junior analysts and share best practices.
• Keep up with emerging evidence synthesis methods and AI-assisted review practices.