> Markdown version of [/jobs/ext/2689475-information-architect](https://www.wearedevelopers.com/jobs/ext/2689475-information-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Information Architect - **Company:** CareerCircle - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $142,400.0 - $224,100.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Bioinformatics, Business Process Modeling, Data Architecture, Electronic Data Capture, Graph Database, Information Sciences, Laboratory Information Management Systems, Meta-Data Management, Operational Data Store, Raw Data, Resource Description Framework (RDF), Requirements Management, Semantic Web, SPARQL, Data Lakes, Information Technology, Data Management, Workday, GXP - **Published:** September 3, 2026 - **Apply:** https://www.careercircle.com/jobs/all/all/usa/pa/west-point/44f4472a-77fc-4ae5-9796-e31fce582122 ## About the Role * Education: Bachelor's or Master's degree in Life Sciences, Computer Science, Bioinformatics, Information Science, or a related field. * 5+ years of experience as an Information Architect or similar role within the Biopharmaceutical or Life Sciences industry. * Proven, hands-on experience working with industry-standard scientific ontologies, semantic web technologies (RDF, OWL, SPARQL), and knowledge graphs. * Hands on experience working with stakeholders to understand data needs in support of insights and defining data models to deliver reusable data products for a spectrum of needs * Domain Knowledge: * Deep understanding of pre-clinical discovery workflows and manufacturing process/method development. * Strong familiarity with dominant lab data capture solutions (LIMS, ELN, CDS, and lab endpoint software). * Experience with industrial time-series data and contextualization tools (e.g., OSIsoft PI). * Technical Skills: * Hands on experience with data modeling tools * Hands on experience with ontology management tools such as CENTree * Excellent analytical, problem-solving, and communication skills, with the ability to bridge the gap between scientific stakeholders and technical engineering teams., Business Enterprise Architecture (BEA), Business Process Modeling, Data Management, Data Modeling, Data Science, Requirements Management, Stakeholder Relationship Management, Strategic Planning, System Designs, Technical Advice ## Description OSIsoft Research Metadata Management Innovation Data Lakes Compassion Ontologies Time Series Data Capture Data Science Semantic Web Communication Life Sciences Data Modeling Problem Solving Data Management Computer Science Telephone Skills Domain Knowledge Data Architecture Biopharmaceuticals Strategic Planning Workday (Software) Raman Spectroscopy Method Development Workflow Management Contingent Workforce Technical Engineering Operational Data Store Manufacturing Processes Artificial Intelligence Relationship Management Enterprise Architecture Requirements Management Information Architecture Business Process Modeling Resource Description Framework (RDF) SPARQL Protocol And RDF Query Language (SPARQL), We are seeking a highly skilled Senior Information Architect to lead the design, organization, and standardization of scientific data spanning across pre-clinical discovery and manufacturing process and method development. In this critical role, you will be responsible for working with scientists and scientific leaders to understand information needs of biopharma innovation and help define information architectural constructs (Ontologies and data models), controls and processes to improve quality and context of data in support of innovation. You will partner closely with R&D scientists, process engineers, and IT teams to harmonize complex biological, chemical, and operational data-from raw scientific outputs to GxP-compliant manufacturing data lakes., * Work with stakeholders to understand their key outcome needs and Insights from data that can support these outcomes * Embed in product teams enabling capture and consumption of scientific data, to help define/adopt ontologies and data models that support capture and consumption of data in service of these research outcomes * Working as a part of data capture product team, be a voice of activation for, and help define standards and controls for data and metadata to improve quality and context of data at capture * Lead the adoption and integration of industry-standard ontologies (such as BioAssay Ontology (BAO) and others) to contextualize scientific datasets (e.g., Raman spectra raw data, assay results) and manufacturing process parameters. * Develop and maintain best practices for capturing current state of information capture and consumption for entities relavent to research processes to help improve investment in data, OSIsoft Research Metadata Management Innovation Data Lakes Compassion Ontologies Time Series Data Capture Data Science Semantic Web Communication Life Sciences Data Modeling Problem Solving Data Management Computer Science Telephone Skills Domain Knowledge Data Architecture Biopharmaceuticals Strategic Planning Workday (Software) Raman Spectroscopy Method Development Workflow Management Contingent Workforce Technical Engineering Operational Data Store Manufacturing Processes Artificial Intelligence Relationship Management Enterprise Architecture Requirements Management Information Architecture Business Process Modeling Resource Description Framework (RDF) SPARQL Protocol And RDF Query Language (SPARQL) +0 Assoc. Dir , Information Architecture Merck & Co., Inc West Point, PA*On-Site Biology OSIsoft Research Metadata Management Innovation Data Lakes Compassion Ontologies Time Series Data Capture Data Science Semantic Web Communication Life Sciences Data Modeling Problem Solving Data Management Computer Science Telephone Skills Domain Knowledge Data Architecture Biopharmaceuticals Strategic Planning Workday (Software) Raman Spectroscopy Method Development Workflow Management Contingent Workforce Technical Engineering Operational Data Store Manufacturing Processes Artificial Intelligence Relationship Management Enterprise Architecture Requirements Management Information Architecture Business Process Modeling ## Related Videos - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Destigmatizing the Workplace: Building Real Inclusion](https://www.wearedevelopers.com/videos/1492-destigmatizing-the-workplace-building-real-inclusion) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [WeAreDevelopers LIVE - How DevRel Makes Tech More Human](https://www.wearedevelopers.com/videos/2149-wearedevelopers-live-how-devrel-makes-tech-more-human) - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [The Future of Employee Wellbeing: Benefits, Trust & Performance](https://www.wearedevelopers.com/videos/1808-the-future-of-employee-wellbeing-benefits-trust-performance) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)