Data Discovery and Enrichment Expert- Material Chemistry

Elsevier; Gurugram District; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Elsevier is seeking a Data Discovery and Enrichment Expert in Materials Chemistry to merge chemistry expertise with GenAI search practices, optimizing how users find and retrieve chemistry information. You will help shape AI-driven search capabilities for Reaxys and related platforms, collaborating with data science and technology partners.

The role focuses on designing evaluation datasets, validating content quality, and refining data models to improve discovery in materials science, polymers,

Qualifications

• PhD or post-doctoral experience in Materials Chemistry, Polymer Chemistry, or a closely related field.
• Understanding of materials science applications and the kinds of data valued by researchers in related industries.
• Ability to design evaluation datasets and assess the quality of extracted content.
• Knowledge of how materials chemistry data is stored, structured, and retrieved in scientific information systems.
• Strong analytical and communication skills and collaboration with scientific/technical partners.

Responsibilities

• Support content enrichment activities, including manual and AI-assisted extraction for materials chemistry content.
• Provide subject-matter guidance on content types, data elements and use cases valuable to customers in materials science and related industries.
• Draft guidelines on content extraction and data normalization for researchers and industry partners.
• Perform data analysis and create reports to support content strategy and prioritization.
• Ensure quality assurance of materials chemistry data.

Skills

GenAI search

Chemistry knowledge

Data enrichment

Content extraction

Quality assurance

Education

PhD or post-doctoral in Materials Chemistry

Job description

Job Summary

Data Discovery and Enrichment Expert - Material Chemistry

Do you enjoy combining chemistry expertise with GenAI search techniques to help users find the right scientific information faster?

Are you excited about shaping how researchers search, retrieve, and interact with chemistry data using next-generation AI solutions?

About our Team

Our team transforms scientific information into structured data and works closely with Data Science and Technology partners to design, train, and validate new AI-driven search capabilities. Together, we contribute our expertise to deliver innovative solutions that enhance how chemistry knowledge is discovered.

About the Role

As a Data Discovery and Enrichment Expert, you will bring chemistry expertise together with GenAI search practices to optimise how users find and retrieve chemistry information. You will help design and evaluate GenAI-based search behaviours, create high-quality test sets for training and validation, and collaborate with Data Science and Technology partners to shape new AI search solutions for Reaxys.

Responsibilities

• Support content enrichment activities, including both manual and AI-assisted automated content extraction, with a focus on materials chemistry content.
• Provide subject-matter expertise on content types, data elements, and use cases of value to customers in materials science and related industries beyond traditional small-molecule pharma (e.g., polymers, batteries, catalysts, semiconductors, advanced materials).
• Draft guidelines on content to be extracted and data normalization approaches that meet the needs of materials science researchers and industry partners.
• Perform data analysis and create data reports to support content strategy and prioritization decisions.
• Perform quality assurance of materials chemistry data.

Requirements

• PhD or post-doctoral experience in Materials Chemistry, Polymer Chemistry, or a closely related field, with hands-on laboratory or research experience.
• Understanding of materials science applications and industries (e.g., energy storage, polymers, catalysis, semiconductors, or advanced materials) and the types of data and content valued by professionals in these fields.
• Ability to design evaluation datasets and assess the quality of extracted content.
• Understanding of how materials chemistry data is structured, represented, and retrieved in scientific information systems (e.g., databases, taxonomies, or similar platforms).
• Strong analytical and communication skills, with the ability to collaborate effectively with scientific and technical partners.