Associate Director, Evidence Generation Study Execution & Data Group Lead

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Job Description

Role Objectives:

• Lead the Evidence Generation Study Execution & Data capability within the Bengaluru GCM, overseeing governance records and systems operations, AI-enabled surveillance, RWD data operations, statistics and analysis, post-hoc / SAP trial-data analysis, internal study execution and study-development support
• Establish a scalable operating model that delivers high-quality operational execution, documentation, coordination, analytics support, and repository discipline that enables Global Evidence Generation and RWD leadership to focus on scientific strategy, methodology, interpretation, and final decision-making

Key Responsibilities:

Capability Leadership & Operating Model Build

• Establish operating rhythms, role clarity, escalation pathways, and quality expectations across the Study Execution & Data GCM teams
• Oversee team delivery across governance records and systems operations, AI-enabled surveillance, RWD data ingestion and quality, statistics and analysis, post-hoc trial-data analysis, internal study execution and study-development support
• Manage daily workflows for manager level roles related to RWD activities including data ingestion and analysis
• Define capacity plans, intake rules, workload allocation, and handoff protocols with Global Evidence Generation, RWD CoE, DD&T, R&D, I&A, LOCs, and other partners
• Ensure GCM execution remains within approved scope while strategic judgment, scientific interpretation, methodology decisions, and final approvals remain with US owners

Data, AI & Systems Oversight

• Oversee evidence data governance support, repository validation, data access assessment, systems roadmap implementation support, and AI-enabled literature surveillance
• Ensure data governance and systems activities follow defined metadata, access, version-control, retention, and audit-readiness standards
• Partner with DD&T, R&D, and I&A to support implementation planning, testing, readiness, communication, and change documentation for Evidence Generation systems and data capabilities
• Monitor risks related to data access, repository quality, system dependencies, AI output traceability, and unresolved technical or governance issues

Study Execution & Analytical Delivery Oversight

• Oversee GCM support for statistics and analysis, post-hoc / SAP trial-data analysis, internal study execution, evidence-source landscaping, protocol / synopsis support and study-execution documentation
• Ensure analytical and study execution outputs include documented assumptions, limitations, QC evidence, reproducibility records, and escalation notes
• Support standardization of templates, trackers, output shells, review packages, and documentation workflows
• Escalate methodology changes, interpretation questions, scientific issues, regulatory / HTA implications, and strategic tradeoffs to Global Evidence Generation owners

Team & Stakeholder Management

• Lead and develop Senior Managers and Manager-level ICs; support onboarding, training, coaching, and capability maturation
• Serve as the senior GCM contact for Study Execution & Data delivery, providing status reporting on capacity, quality, backlog, risks, and transition readiness
• Drive continuous improvement, automation adoption where approved, and process standardization across the capability

Qualifications:

Experience: >8 years of related work experience; >4 years of experience in the biopharmaceutical industry; >4 years in evidence generation, RWE / HEOR, clinical operations, study execution, data governance, analytics operations, or medical affairs operations. Experience managing teams or senior individual contributors preferred.

Technical skills:

• Strong understanding of evidence generation study execution, RWD / HEOR operations, data governance, study systems, and analytical delivery workflows
• Ability to lead cross-functional delivery across Global Evidence Generation, RWD CoE, DD&T, R&D, I&A, LOCs, and vendors
• Knowledge of study documentation, repository governance, QC evidence, audit readiness, and controlled analytics environments
• Familiarity with RWD data sources, study systems, AI-enabled surveillance, SAS / R / SQL workflows, Veeva, iEnvision, or equivalent platforms preferred
• Strong stakeholder management, operational governance, and process scale-up skills

Education: A scientific, medical, life sciences, pharmacy, public health, epidemiology, biostatistics, data science, or health economics degree is required; advanced degree preferred

Languages: Fluent English required; additional languages advantageous

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