Clinical Trial Manager

Job Title: Project Manager / Clinical Trials Data Modeling Lead Company: NeevSys Inc. Location: Remote / Hybrid, U.S. preferred Employment Type: Part-Time or Consultant Role Overview NeevSys is seeking a Project Manager / Clinical Trials Data Modeling Lead to support an FDA‑facing proof of concept focused on protocol extraction, protocol comparison, validation, ontology alignment, reviewer feedback, source citation, confidence scoring, and reviewer‑facing displays. This is a blended role that combines project management, clinical trial protocol expertise, and senior data modeling responsibilities. The selected candidate will manage project execution across NeevSys, Deloitte, CTIS, and FDA stakeholders while also leading data modeling activities for extracted protocol elements, ICH M11‑aligned sections, historical protocol comparisons, ontology references, validation outputs, and reporting structures. Key Responsibilities Project Management and Stakeholder Coordination Manage contract execution, project planning, schedule control, risk management, stakeholder coordination, deliverables, financial reporting, and POC demonstration readiness. Develop and maintain the Project Management Plan, milestone schedule, staffing coordination plan, assumptions log, risks, dependencies, and decision tracker. Lead bi‑weekly progress meetings, capture meeting minutes, track decisions, and manage action items through closure. Prepare monthly progress reports covering deliverable status, completed work, upcoming work, risks, issues, dependencies, financial summary, and next actions. Track dependencies related to onboarding, FDA access, Elsa environment availability, historical protocol data, SME availability, technical inputs, validation cycles, and POC demonstrations. Coordinate AI/NLP, data modeling, ontology, clinical SME, application development, and documentation workstreams to keep deliverables aligned to the PWS. Support labor‑hour tracking, burn‑rate monitoring, subcontractor coordination, and client‑facing status reporting. Clinical Trials and Protocol Review Support Provide clinical trial protocol, regulatory, and reviewer workflow expertise for the POC. Guide how extracted protocol elements, ICH M11 sections, legacy protocol sections, ontology references, confidence scores, citations, validation outputs, and reviewer‑facing displays should support protocol review. Validate whether extracted protocol elements align with reviewer expectations and clinical trial context. Support mapping of legacy protocol sections to ICH M11‑aligned structures. Define review scenarios for historical protocol comparison, gap identification, consistency checks, validation, and reporting. Provide SME input on clinical terminology, controlled vocabulary, ontology usage, and reviewer feedback capture. Review POC outputs for clinical usability, completeness, traceability, and reviewer‑facing clarity. Data Modeling and Technical Coordination Lead conceptual and logical data modeling for protocol extraction, comparison, validation, reviewer feedback, source citation, and reporting outputs. Define entity relationships for protocols, M11 sections, legacy sections, extraction fields, ontology terms, confidence scores, citations, validation results, and reviewer feedback. Create source‑to‑target mapping tables, data dictionaries, traceability matrices, and data‑flow views. Model semi‑structured document extraction outputs, reviewer feedback loops, ontology mappings, confidence scoring, metadata, and citation traceability. Guide the Data Modeler and Application Developer in implementing POC‑ready data structures. Document modeling assumptions, unresolved data gaps, metadata dependencies, clinical interpretation issues, validation findings, and recommendations for option‑year expansion. Required Qualifications 8+ years of experience in project management, clinical trial operations, data modeling, healthcare data, life sciences, regulatory systems, analytics, or federal IT programs. Experience managing schedules, risks, issues, action items, deliverables, subcontractors, client communications, and monthly status reporting. Strong understanding of clinical trial protocols, protocol amendments, clinical operations, regulatory review workflows, or structured protocol review. Experience developing conceptual and logical data models, ERDs, data dictionaries, source‑to‑target mappings, canonical models, metadata models, and data lineage documentation. Ability to model semi‑structured document extraction outputs, reviewer feedback data, ontology mappings, confidence scores, validation results, and citation traceability. Strong written and verbal communication skills for government‑facing reporting, meeting facilitation, documentation, and stakeholder coordination. Ability to work with multidisciplinary teams across AI engineering, NLP, RAG, data standards, ontology, clinical SMEs, application development, and technical writing. Preferred Qualifications Experience with FDA, HHS, NIH, EPLC, CMMI, federal BPA/task order environments, or regulated health IT programs. Experience supporting POCs, AI/ML projects, data modernization, document extraction, clinical systems, regulatory systems, or reviewer‑facing applications. Familiarity with ICH M11, CDISC, FHIR, clinical ontologies, controlled terminology, semantic models, or knowledge graphs. Experience with PostgreSQL, SQL, Databricks, vector metadata, ERwin, ER/Studio, Jira, SharePoint, Confluence, or ServiceNow. PMP, Agile/Scrum, clinical research, healthcare data, regulatory submission, or data architecture experience. Experience with labor‑hour pricing, financial tracking, burn‑rate monitoring, and subcontractor coordination. Ideal Candidate The ideal candidate can manage a federal‑facing POC while also understanding clinical trial protocol content and data modeling needs. This person can translate reviewer workflows into practical data structures, coordinate technical and clinical teams, track delivery execution, and help prepare a working POC for stakeholder demonstrations. #J-18808-Ljbffr