TetraScience

Architect

• Architect the Exchange Layer: Design and own the Common Data Models (CDMs) that serve as the universal language for scientific data across our customer base. Move the platform from bespoke, one-off mappings to a standardized "exchange layer" that ensures interoperability.
• Empower Forward Deployed Engineering: Create the data contracts and standardized definitions that FDEs rely on. Your models will be the toolkit that allows them to deploy faster and with higher confidence, knowing they are building on a stable, consistent semantic foundation.
• Standardization vs. Flexibility: Strike the strategic balance between rigid global standards (for cross-customer exchange) and local flexibility. Define the core "immutable" aspects of the model versus where extension is permitted.
• The "Forest" – Business Alignment: Translate high-level business goals (e.g., "accelerate time-to-insight for biologics") into concrete data modeling strategies. Ensure our semantic roadmap directly supports the scientific questions our customers—and our internal teams—need to answer.
• The "Trees" – Hands-on Modeling: Roll up your sleeves to design and implement complex ontologies and taxonomies. Model intricate scientific relationships (e.g., linking a "Cell Line" in an ELN to "Flow Cytometry Results") with precision.
• Software & Data Engineering Integration: Work directly with Engineering to architect the software systems that consume these models. Ensure that the "perfect" ontology does not break query performance or system scalability.
• Data Contracts & Governance: Establish the "rules of the road" for data quality and consistency. Define how data contracts are versioned, enforced, and evolved, ensuring that downstream consumers (AI teams, FDEs, Scientists) can trust the data structure.
• Scientific Translation: Partner with Scientific Business Analysts to decode the complexity of biopharma R&D. Turn ambiguous scientific requirements into rigorous, machine-readable data structures.
• Interoperability: Architect models that ensure our data is FAIR (Findable, Accessible, Interoperable, Reusable) and ready for downstream AI/ML applications.

Data & Semantic Model Architect

Engineer

• Apply Lessons Learned From Domain Leaders: Bring practical, everyday lessons learned and experiences from other areas, domains and professions to this problem space.
• Engineer Semantic Services: Co-design and build the Service-Oriented Architecture (SOA) components responsible for the lifecycle of semantic data. Your software enables ingestion, abstraction, curation, and publication, versioning, governance & distribution of semantic resources—encompassing formal biomedical ontologies, standard terminologies, and reference lists—integrating them directly into data-in-flight services.
• Data Engineering for Continuous Modeling: Develop and deploy ETL pipelines that lift instance-level data into formal vocabularies. You will ensure these pipelines capture the nuanced aspects of the model, including complex relationships, properties, and constraints.
• Living Ontology Development: Build services that project formal semantic meaning across the Tetra ecosystem, helping to formalize a "living," real-world ontology that evolves with our data and its usage.
• Partner as a Force Multiplier: Collaborate with Scientific Data Engineers, Architects, and Business Leads to integrate semantic artifacts technically. You will provide subject matter expertise, coaching, and training on the governance of controlled vocabularies, ensuring formal semantics and structure are applied consistently across platform applications.
• Vocabulary Management: Develop software enabling management of the full lifecycle of our formal vocabularies. You will implement robust systems for versioning, deprecating, and migrating vocabularies across our customer base to ensure seamless operations.
• Engineering Mentorship: Serve as the "Informatics SME" for the engineering organization. You will partner with and mentor technical team members—ranging from pure software engineers to scientists—on how to leverage semantic artifacts to provide data with formal definitions, meaning, and context.
• Data Exchange Standards: Co-design the "handshake" protocols for data exchange between platform components. You will iteratively develop these standards to ensure that data leaving one system is deterministically understood by another, handling the complex mapping and transformation logic required for true syntactic and semantic interoperability.

Data & Semantic Model Architect

Senior Informatics Engineer