Information Scientist – Content Analytics
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Job Summary
Are you ready to shape the future of biomedical information Join a dynamic and innovative team at the forefront of scientific discovery where your passion for information science and curiosity about artificial intelligence will drive meaningful impact. As an Information Scientist specializing in Content Analytics youll harness advanced AI tools and data analytics to unlock insights from the worlds biomedical literature. Your expertise will help design smarter workflows champion ethical and responsible AI practices and enable cross-functional collaboration across pharmaceutical R&D. If you thrive in a fast-evolving environment love exploring new technologies and want to empower others through training and knowledge sharing this is your chance to make a difference
Key Responsibilities
Content Analytics & Knowledge Management:
o Design and implement workflows for literature mining summarization and trend analysis using AI/NLP tools.
o Develop and maintain external information endpoints ensuring FAIR principles (Findable Accessible Interoperable Reusable) and interoperability.
AI & Advanced Analytics:
o Apply machine learning and large language models (LLMs) to enhance information retrieval and automate content classification.
o Research and propose innovative AI solutions for scientific content analysis.
Information Science:
o Support pharmaceutical R&D processes.
o Apply knowledge of data lifecycle metadata ontologies and scientific knowledge systems.
o Ensure data is structured for scientific use leveraging FAIR data principles and semantic technologies.
Collaboration & Stakeholder Engagement:
o Partner with cross-functional teams as required.
o Act as a subject matter expert for AI-driven content analytics initiatives.
Governance & Compliance:
o Ensure adherence to copyright licensing and data governance standards for external and internal content.
o Implement robust data integrity measures and maintain audit trails for AI-driven processes.
Training & Enablement:
o Provide training on AI/NLP tools and best practices for content analytics.
o Develop guidelines and competency frameworks for upskilling in digital and data science capabilities through the application of content analytics.
Key Responsibilities
Content Analytics & Knowledge Management:
o Design and implement workflows for literature mining summarization and trend analysis using AI/NLP tools.
o Develop and maintain external information endpoints ensuring FAIR principles (Findable Accessible Interoperable Reusable) and interoperability.
AI & Advanced Analytics:
o Apply machine learning and large language models (LLMs) to enhance information retrieval and automate content classification.
o Research and propose innovative AI solutions for scientific content analysis.
Information Science:
o Support pharmaceutical R&D processes.
o Apply knowledge of data lifecycle metadata ontologies and scientific knowledge systems.
o Ensure data is structured for scientific use leveraging FAIR data principles and semantic technologies.
Collaboration & Stakeholder Engagement:
o Partner with cross-functional teams as required.
o Act as a subject matter expert for AI-driven content analytics initiatives.
Governance & Compliance:
o Ensure adherence to copyright licensing and data governance standards for external and internal content.
o Implement robust data integrity measures and maintain audit trails for AI-driven processes.
Training & Enablement:
o Provide training on AI/NLP tools and best practices for content analytics.
o Develop guidelines and competency frameworks for upskilling in digital and data science capabilities through the application of content analytics.
Requirements
Core Skills & Competencies
Technical Skills:
o Experience or interest in NLP and LLM applications (transformers Retrieval-Augmented Generation prompt engineering)
o Familiarity with data visualization and scientific communication tools
o Knowledge graph and ontology management
o Python and AI frameworks for text analytics
Soft Skills:
o Cross-functional collaboration
o Project management and stakeholder communication
o Adaptability to emerging technologies
Technical Skills:
o Experience or interest in NLP and LLM applications (transformers Retrieval-Augmented Generation prompt engineering)
o Familiarity with data visualization and scientific communication tools
o Knowledge graph and ontology management
o Python and AI frameworks for text analytics
Soft Skills:
o Cross-functional collaboration
o Project management and stakeholder communication
o Adaptability to emerging technologies
Required Skills:
Responsible for overseeing the strategy governance and quality of all master data (Vendors Customers Materials) ensuring its accuracy consistency and alignment with business processes across the organization. Requirements: 10 years of experience in global data depth knowledge in Master Data Governance and Strategy Expertise in Data Quality Management knowledge in Data Integration and Architecture Change Management and Data Migration
Company Industry
IT Services and IT Consulting
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
