Scientific Article Data Reviewer

Company Description Bioz is a science-focused technology company that delivers an evidence-based intelligence layer derived from extensive analysis of the scientific literature. Its proprietary, data-driven rating system highlights which reagents, instruments, tools, and research services are most strongly supported by real experimental use and outcomes. By improving product selection, Bioz helps researchers strengthen reproducibility, reduce trial-and-error, and accelerate the journey from idea to result across industry, academia, healthcare, government, and diverse scientific fields. Bioz also serves suppliers through a badge platform that displays literature-based validation alongside their products, increasing credibility, conversion, and engagement at the point of decision. This dual value proposition positions Bioz as a trusted partner to both researchers and suppliers seeking objective, evidence-backed product insights.

Role Description The Scientific Article Data Reviewer is a remote role focused on analyzing scientific publications to extract, validate, and structure experimental data for Bioz’s intelligence platform. In this role, the reviewer will read peer-reviewed articles, identify relevant methods, materials, and outcomes, and accurately classify products, reagents, and tools used in experiments. The position involves checking data for consistency, completeness, and accuracy, applying standardized annotation guidelines, and flagging any discrepancies or missing information. The reviewer will collaborate with internal teams to refine data-entry protocols, maintain documentation of review decisions, and contribute feedback to improve automated text-mining and analytics workflows. This role requires consistent, detail-oriented work within defined timelines and adherence to quality standards while working independently.

Qualifications

• Priority will be given to students and research staff.
• Scientific domain skills: Strong background in life sciences or related fields (e.g., biology, biochemistry, molecular biology, pharmacology) with the ability to understand experimental design, methods, and results.
• Technical and digital skills: Comfort working with web-based tools, databases, spreadsheets, and documentation platforms; ability to learn new software systems and workflows quickly.
• decisions, provide constructive feedback, and collaborate asynchronously with distributed teams.
• Education and experience: B.Sc/ M.Sc student.
• Work style: Ability to work independently in a remote setting, manage part-time hours reliably, and meet deadlines while adapting to evolving processes.