Head of Data Intelligence

About the Position

Lead and build the Data Intelligence function that ingests, validates, harmonizes and serves collaborator and internal data - including data for a production clinical component - to power ML/LLM research and product workflows. Hands-on technical leader who owns data platform, LLM/tooling orchestration, clinical/biological/chemical fidelity, and regulatory/QMS-ready governance.

Core responsibilities

• Own end-to-end internal multimodal data platform (collaborators’ EHR, imaging, omics, assays).
• Design, build and validate the clinical data environment (generation, augmentation, fidelity metrics and privacy safeguards) for model training and experiments.
• Architect, deploy, and operate robust LLM systems and tools to structure data and reach the company's KPIs. Execute rigorous evaluation pipelines (hallucination guardrails, accuracy, and reliability tracking).
• Hire and lead a cross-functional team (data engineering, clinical annotators, bioinformatics) and own standards and tech choices.
• Partner with clinical, product, compliance and bizdev teams to translate domain requirements into systematically defined data products.
• Lead secure, auditable collaborator data transfer onboarding: schema mapping, transfer, de-identification, provenance (data lineage), and monitoring.

Must-have qualifications

• Proven leader of cross-functional technical teams
• 5+ years building and operating large data platforms/pipelines; demonstrable experience with clinical or biomedical datasets, data lakehouses.
• 3+ years of building Multimodal data pipelines, schema, and data harmonization.
• MS/PhD in CS, Bioinformatics, Computational Biology, Biomedical Engineering or clinical/chemical discipline.
• Strong software & data engineering skills: Python, SQL, orchestration, Docker, data modeling, modern data lakehouse, and large-scale data processing.
• Experience with Linux environment and CLI tools for data transfer.
• Familiarity with object storage and cloud providers (AWS/GCP/Azure/OCI).

A Significant Advantage

• Hands-on production experience with LLMs and LLM tooling (RAG, orchestration, tool integrations, evaluation, prompt engineering).
• Domain experience in oncology, immunology, assays or pharma/CRO partnerships.
• Experience working with clinical data models and standards (e.g., FHIR/HL7, OMOP, ICD, SNOMED, LOINC, CDISC) in real-world datasets.
• Experience implementing data catalogs and lineage tools.