Sr Biomedical Scientific Data Quality Expert

Elsevier; Gurugram District; On-site; INR 1,200,000 - 2,100,000; Full time

Job summary

Elsevier in India is seeking a Senior Biomedical Scientific Data Quality Expert to independently drive scientific content quality and validation for life-sciences information products. You will interpret biomedical and chemical information, analyze outputs from large datasets, and assess the accuracy, consistency, completeness, and relevance of content.

You will help define quality standards, identify root causes, and provide evidence-based recommendations to product, data, and engineering

Qualifications

• Advanced degree or equivalent in pharmacoinformatics, pharmacology, pharmaceutical sciences or related field.
• Strong knowledge of scientific data-quality standards and methods for evaluating Agentic AI outputs.
• Experience with large scientific databases, taxonomies, and ontologies.
• Strong analytical, documentation, and attention-to-detail skills.
• Excellent written and verbal communication skills.

Responsibilities

• Define the scope and approach for scientific content quality and validation projects.
• Design test sets with traceable expected outputs.
• Conduct manual and automated scientific evaluations of AI outputs.
• Analyze outputs from very large scientific datasets to identify error patterns.
• Translate findings into recommendations for cross-functional teams.

Skills

Advanced degree

Data-quality standards

Agentic AI understanding

Analytical skills

Communications

Education

Pharmacoinformatics or related

Bioinformatics

Job description

Senior Biomedical Scientific Data Quality Expert

Do you have experience assessing biomedical and chemical data quality

Can you evaluate scientific data and AI outputs and recommend improvements

Job Summary

You will independently drive detailed scientific content quality and validation activities for life-sciences information products. Your focus will be interpreting biomedical and chemical information, analyzing outputs from very large scientific datasets, and assessing the accuracy, consistency, completeness, and relevance of content. You will help define quality standards, identify root causes, and provide evidence-based recommendations to product, data, and engineering teams.

We are a diverse and dedicated team working on life-sciences data and digital solutions. We maintain services that support research across drug discovery, development, safety, and healthcare. Our mission is to ensure scientific content is accurate, well organized, and trustworthy. We build AI-driven products people can rely on. We focus on data integrity, reliable insights, teamwork, and continuous learning across disciplines.

Responsibilities

• Define the scope and approach for scientific content quality and validation projects.
• Design representative, edge-case, and challenge test sets with traceable expected outputs.
• Conduct manual and automated scientific evaluations of Agentic AI outputs.
• Analyze outputs from very large scientific datasets and identify systematic error patterns.
• Translate evaluation findings into clear, documented recommendations for cross-functional teams.

Requirements

• Advanced degree or equivalent experience in pharmacoinformatics, pharmacology, pharmaceutical sciences, bioinformatics, medicinal chemistry, or a related discipline.
• Strong knowledge of scientific data-quality standards and methods for evaluating Agentic AI outputs.
• Experience with large scientific databases, taxonomies, and ontologies.
• Strong analytical, documentation, and attention-to-detail skills.
• Sound technical understanding of agentic AI systems, APIs, GitHub, or comparable tools.
• Excellent written and verbal communication skills.

Work in a way that works for you

We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.

• Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive