Structure Networks, Inc.

Director

• Support and help advance model-informed drug development (MIDD) across discovery and development programs.
• Represent Pharmacometrics on cross-functional teams, providing quantitative input to strategy, dose selection, and trial design; influence decisions through data-driven recommendations.
• Plan, execute, and document pharmacometrics analyses (PopPK/PKPD/exposure–response), including models, simulations, and reports.
• Develop and maintain Shiny-based applications to enable data visualization and model-based simulation workflows, with potential integration of AI/ML-enabled features as appropriate.
• Coordinate and oversee external vendors/consultants and review deliverables for quality and timeliness.
• Contribute to pharmacometrics elements of regulatory submissions and health authority responses, with guidance from function leadership.
• Support functional process improvements (e.g., templates, workflows, and modeling infrastructure) and other needs (e.g., due diligence) as assigned.

Director, Pharmacometrics

Data Engineer

• Define and execute a unified enterprise data strategy aligned with corporate objectives across the full Structure ecosystem (pre‑clinical, clinical, G&A)
• Lead modernization of data platforms—cloud data lakes/warehouses, data mesh or lakehouse architectures, master data solutions, and advanced analytics infrastructure
• Establish data governance frameworks encompassing privacy, compliance (e.g., GxP, 21 CFR Part 11, HIPAA), and high data quality standards
• Architect scalable, secure, and high-performance infrastructures for structured and unstructured data with clear data models, taxonomies, and semantic layers
• Lead implementation of robust ETL pipelines, real-time ingestion (streaming), integration, and transformation processes across internal and external sources
• Establish data governance with legal, compliance, and business teams
• Enable data cataloging, lineage, and metadata management for easy discovery and tracking
• Apply CI/CD, observability, monitoring, and reliability to data pipelines in regulated environments
• Ensure operational excellence through robust SLAs, effective incident management, and scalable performance
• Collaborate with R&D, Clinical, Commercial, and G&A teams to deliver tailored data solutions supporting scientific insight, clinical analytics, commercial intelligence, and administrative decision-making
• Facilitate self-service analytics and data democratization initiatives
• Integrate data platform capabilities to support AI/ML lifecycle—data provisioning, ML Ops, model feature stores, deployment, and monitoring
• Build, mentor, and inspire a high-performing team of architects, engineers, and operations professionals
• Cultivate a data-driven culture of innovation, quality, accountability, and cross-functional collaboration

Director, Pharmacometrics

Senior Director, Data Engineering – Architecture