TetraScience · 1 day ago
Data & Semantic Model Architect
United States
Full-time
Remote
Senior Level
7+ years expTetraScience is a leading Scientific Data and AI company driving the Scientific AI revolution through innovative lab data management solutions. The Data & Semantic Model Architect will be responsible for overseeing the Common Data Model and Exchange Layer, ensuring seamless data flow across customer environments and enabling rapid integration for scientific insights.
BiotechnologyBig DataSoftwarePharmaceuticalInternet of ThingsLife ScienceData IntegrationData Management
Responsibilities
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
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
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
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
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
Partner with Scientific Business Analysts to decode the complexity of biopharma R&D. Turn ambiguous scientific requirements into rigorous, machine-readable data structures
Architect models that ensure our data is FAIR (Findable, Accessible, Interoperable, Reusable) and ready for downstream AI/ML applications
Proven ability to design shared data models that serve as an exchange format between different systems or organizations. You understand the challenges of mapping heterogeneous source data into a single, unified target schema
Experience defining and enforcing data contracts in a microservices or platform environment. You know how to create specifications that developers and FDEs can build against reliably
The ability to switch context effortlessly between high-level system design (software architecture) and low-level entity relationship modeling
Deep, hands-on expertise with semantic web standards (RDF, OWL, SHACL, SPARQL) and property graph concepts (LPG)
Qualification
Required
7+ years of experience in data architecture, informatics, or technical product leadership, specifically within life sciences, healthcare, manufacturing technology or the ability to demonstrate complex, multidomain unification of data models & semantic layers
CDM Framework Expertise: Direct, hands-on experience implementing and extending Common Data Model frameworks such as HL7 FHIR, OMOP (OHDSI), Allotrope, or CDISC. You should know the strengths and limitations of each for biopharma R&D
Terminology & Standardization: Proven mastery in standardizing messy, heterogeneous data using both standard vocabularies (such as terminology standards & ontologies) as well as proprietary or custom vocabularies. You must have experience semantically curating (semantic mapping & aggregation; ie value set creation) between and across vocabularies as well as discrete instance data
Platform & Exchange Experience: Experience building data platforms where standardization and reusability were key value drivers. You have likely built models that serve as an exchange layer across multiple customers
Technical Background: Strong proficiency in software development concepts; you should be comfortable reading code, understanding API contracts, and discussing database internals
Education: Bachelor's or Master's +in a relevant field (e.g., Medical Informatics, Computer Science, Bioinformatics, Physics)
Company
TetraScience
TetraScience is an R&D cloud data management company that empowers transformation in life sciences and drug discovery.
201-500 employees
H1B Sponsorship
TetraScience has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (2)
2023 (3)
2022 (2)
2021 (1)
2020 (3)
Funding
Current Stage
Growth StageTotal Funding
$99.14MKey Investors
Alkeon Capital,Insight PartnersUnderscore VCWaters
2021-04-15Series B· $80M
2020-05-01Series A· $11M
2019-10-31Series A· $8M
Leadership Team
Patrick Grady
CEO
Siping Wang
President & CTO
Recent News
Research & Development World
2026-01-16
Company data provided by crunchbase