Product Data and Content Manager - Recombinant Proteins

Overview

Lead the processes, standards, and cross-functional coordination needed to make recombinant protein products accurate, complete, and ready for launch across customer-facing catalogues and purchasing platforms.

What you'll do

• Develop and implement an AI-tailored strategy for findability.
• Own the product data and content readiness process for new and existing recombinant protein products, from information gathering through validation, approval, and publication in web catalogues and purchasing platforms.
• Translate product, supplier, and technical information into complete, usable product records with rich scientific evidence, including product attributes, documentation, images, applications, and other required catalogue content.
• Establish portfolio-wide standards and controls for data quality, content completeness, naming, taxonomy, and change management across thousands of proteins and associated SKUs.
• Lead launch-readiness planning and prioritization, coordinating dependencies with Product Management, R&D, Business Development, Operations, Program Management, and external suppliers.
• Build scalable workflows and tools for collecting, validating, and maintaining high-volume product data; identify automation opportunities and reduce manual rework.
• Monitor readiness and quality through clear metrics, such as content completeness, data accuracy, time to publish, launch delays attributable to missing information, and backlog.
• Identify systemic content and data gaps across the portfolio and lead corrective actions with the relevant teams.
• Lead cross-functional improvements to catalogue and purchasing-platform content, representing customer usability and scientific accuracy in those initiatives.
• Provide expert review and escalation support for complex product-content questions and customer concerns, partnering with technical and commercial teams as needed.
• Guide colleagues and stakeholders on data standards, content expectations, and effective submission practices.

What you'll need

• Advanced degree in life sciences, biotechnology, bioengineering, or a related field; equivalent relevant experience may be considered.
• Experience in product information, scientific content, portfolio operations, product management support, data governance, or a related role in life sciences, biotech, pharma, or research tools.
• Experience preparing and maintaining complex product data for e-commerce, product catalogues, purchasing platforms, PIM systems, ERP systems, or similar content platforms.
• Proven ability to manage large, interrelated datasets and maintain accuracy across many products and SKUs.
• Advanced Microsoft Excel skills.
• Ability to lead cross-functional projects and influence stakeholders across technical, commercial, operations, and digital teams.
• Strong organizational and prioritization skills, including the ability to manage high-volume work while meeting launch deadlines.
• Excellent written communication skills, with the ability to translate technical information into clear, accurate customer-facing content.
• A continuous-improvement mindset, including the ability to identify process gaps, reduce rework, and introduce scalable ways of working.
• Ability to work effectively with external suppliers and internal subject-matter experts to resolve missing, conflicting, or unclear product information.

Nice to have

• Working knowledge of recombinant proteins and their use in laboratory research, with the ability to learn and accurately interpret product specifications, applications, and technical documentation.
• Experience supporting product launches or portfolio expansions in life sciences.
• Experience connecting product data across multiple brands, business units, or product portfolios to support cross-portfolio discovery and customer navigation.
• Experience with taxonomy, search metadata, synonyms, application tags, or other catalogue structures that improve product findability.
• Experience using workflow automation, data quality tools, or AI-assisted methods to improve data preparation and review, with appropriate quality controls.
• Experience with data visualization, database tools, or data transformation and automation.

Details

• Standard office hours (40 per week).
• Office-based role.
• Location: Bangalore, India.