Director, Clinical Data Architecture & RWD Operations

Verily•San Bruno, CA

2d•$182,000 - $273,500

About The Position

Verily is seeking a strategic, clinical-grade operator to lead our Real-World Data (RWD) Operations function. This is a pivotal leadership role responsible for architecting the "Human-in-the-Loop" engine that transforms fragmented, unstructured medical records into regulatory-grade, "Gold Standard" datasets. You will bridge the gap between complex clinical nuance (Hematology, Oncology, Immunology) and technical execution. Your mission is to build a scalable, audit-ready operation that serves as the foundation for Verily’s AI-driven evidence generation.

Requirements

10+ years of experience in clinical data operations, clinical trial management, or real-world evidence (RWE).
Deep Clinical Literacy: Expert understanding of medical terminology, cancer biology, and diagnostic testing (e.g., NGS, flow cytometry, cytogenetics).
Systems Thinking: Proven track record of scaling operations from pilot to production, specifically managing teams of 50+ or high-stakes clinical vendors.
Technical Fluency: Comfort working with Product/Eng teams and a functional understanding of how manual data fuels AI/ML models.

Nice To Haves

Advanced degree (RN, MD, PhD, or MPH) with a focus on clinical informatics or research.
Direct experience with Oncology data or Hematologic Malignancies.
Experience in a high-growth "Health-Tech" or "Biotech" environment.

Responsibilities

Clinical Data Architecture & Governance
Define the Logic: Act as the primary architect of the Clinical Data Dictionary (CDD) and abstraction protocols. You aren't just managing a process; you are defining the clinical rules for "Ground Truth," resolving complex edge cases, and establishing the logic for "inconclusive" or disparate clinical results.
Audit-Ready Provenance: Establish and maintain a rigorous Quality Management System (QMS). Ensure every data point has a verifiable audit trail back to the source EHR, pathology report, or cytogenetic record, meeting the standards required for FDA/EMA submissions.
Ontology Leadership: Drive the standardization of unstructured data into global clinical ontologies (SNOMED CT, LOINC, RxNorm, HGNC, etc.), ensuring data is research-ready and interoperable.
AI-Enabled "Human-in-the-Loop" (HITL) Strategy
Ground-Truth Engineering: Partner with Research and Data Science teams to design high-fidelity labeling tasks that train, validate, and tune machine learning models.
Product Feedback Loop: Act as the lead stakeholder for Internal Product and Engineering teams. You will define the roadmap for internal tooling, identifying where AI-assisted "pre-abstraction" can increase efficiency without sacrificing clinical integrity.
Strategic Vendor & Workforce Management
"Make vs. Buy" Stewardship: Own the unit economics of data generation. Evaluate the ROI of leveraging high-cost clinical vendor experts versus building internal specialized teams or offshore BPO resources.
Vendor Accountability: Manage external Abstraction Vendors against aggressive KPIs, including ≥98% Accuracy, ≥95% Inter-Abstractor Reliability (IAR), and ≥99% Completeness.
Clinical Calibration: Lead regular "Clinical Reconciliation" sessions with vendors to resolve discrepancies in complex data, ensuring external judgment aligns with established standards.
Operational Scaling & Unit Economics
P&L Ownership: Manage the budget for the RWD abstraction function, focusing on driving down "Cost-per-Patient-Record" while maintaining "Gold Standard" quality.
Global Expansion: Design the operational blueprint for scaling beyond US-English EHRs, navigating multi-language abstraction and international regulatory environments.