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Supports the Senior Technical Product Manager in shaping and executing technology product roadmaps for clinical trial planning and execution. Analyzes business needs, writes epics and user stories, prioritizes backlogs, coordinates with engineers and stakeholders, participates in Agile ceremonies, accepts completed stories, manages dependencies, resolves delivery issues, and communicates product progress, risks, and plans.

Leads end-to-end quality assurance for Salesforce, Veeva, and enterprise applications. Defines test strategies, plans, coverage, quality gates, and release criteria; oversees functional, integration, regression, UAT, automation, defect governance, test data, environments, and reporting. Drives Robot Framework automation and AI-enabled testing improvements, ensures audit and QA process compliance, supports go/no-go decisions, and mentors QA teams while coordinating stakeholders, vendors, and offshore teams.

Owns technical architecture, governance, security, operations, and optimization across AWS, Salesforce, and Veeva platforms. Establishes platform inventories, delivery standards, support models, access controls, and compliance processes. Leads vendor release management, automation, CI/CD improvements, AI adoption, prototyping, incident resolution, and root-cause remediation. Partners with global stakeholders and multi-vendor teams to gather requirements, deliver scalable solutions, mentor technical teams, and align platform investments with business objectives.

Lead design and implementation of SAP integrations using SAP BTP and Integration Suite. Migrate legacy PI interfaces, build real-time and batch integrations, implement event-driven architectures, ensure security and compliance, monitor and optimize integrations, create documentation, and act as subject-matter expert to drive automation and digital transformation.

Manage HR system security configuration, access provisioning, data audits, data quality, privacy approvals, and subscription requests. Translate business needs into technical solutions, lead testing and cross-functional projects, troubleshoot complex issues, and improve HRIS processes. Partner with HR Technology, Operations, Privacy, and global stakeholders while supporting Workday and Visier governance in a complex international environment.

Design, build, and maintain scalable data pipelines, services, and backend components; integrate AI/LLM features (chatbots, RAG, copilots) using OpenAI/Anthropic/LangChain; implement APIs, cloud deployments (AWS/Azure), CI/CD, monitoring, and support; collaborate with architects and cross-functional teams in Agile to translate business requirements into enterprise data and AI solutions.

Leads strategy, governance, operational robustness, monitoring, and continuous improvement for clinical supply system integrations, especially SAP, IRT, Veeva, and vendor interfaces. Partners with business owners, IT, SMEs, and vendors to resolve incidents, track KPIs, manage requirements, support releases, and ensure validation, GxP, data integrity, and change-control compliance.

Leads strategy and execution for digital transformation initiatives supporting the Global Clinical Supplies digital roadmap. Owns projects from business-case development through implementation and hypercare, coordinating business, IT, data science, and vendor teams. Drives change management, user adoption, KPI and ROI tracking, and compliance with GxP and software development lifecycle requirements. The role requires extensive pharmaceutical or biotechnology experience, clinical supply chain knowledge, and a strong record delivering complex technology implementations.

Manages cross-functional projects within a biotech manufacturing site's portfolio, including process improvement, system delivery, and new product introduction. Leads project initiation, execution, governance, risk escalation, and continuous improvement of PMO processes. Chairs portfolio governance and risk meetings, applies Waterfall, Agile, or Scrum methodologies, and coaches project leads to strengthen project management capabilities across the organization.

Lead computational analysis of multimodal clinico-genomic datasets across oncology clinical trials and real-world data. Apply statistical learning, deep learning, predictive modeling, and data mining to discover biomarkers, identify novel targets, inform combination strategies, and support molecularly defined patient populations. Analyze genomic, transcriptomic, imaging, epigenetic, single-cell, proteomic, and clinical data while collaborating with AI/ML teams developing foundation models. Communicate data-driven insights to guide pipeline decisions.