Senior Manager, Evidence Generation Statistics & Analytics Group Lead

Location: IND - Bengaluru

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Role Objectives

Lead and oversee the Evidence Generation Statistics & Analytics team covering RWD analysis, statistics and analysis for study design and execution, and post-hoc trial-data analysis. This role provides technical, methodological and operational leadership across the Statistics & Analytics portfolio, ensuring high-quality, fit-for-purpose analytical delivery while final scientific interpretation and approval remain with the accountable Global Evidence Generation or R&D owners.

Serve as the primary escalation point for the team, drive alignment on analytical standards and priorities, and represent the Statistics & Analytics function to senior stakeholders across Global Evidence Generation, Data Governance and other cross-functional partners

Key Responsibilities

Team Leadership & People Management

• Manage, coach and develop a team of Statistics & Analytics Leads spanning RWD analysis, statistics and analysis, and post-hoc trial-data analysis
• Set individual and team performance objectives aligned to portfolio priorities and evidence generation strategy; conduct performance reviews and development planning
• Build team capability and capacity through hiring, training, and succession planning; foster a collaborative, high-performance culture across disciplines
• Allocate team resources across competing study and portfolio priorities, balancing workload and technical fit

Scientific & Methodological Oversight

• Provide senior-level review and quality assurance for RWD analyses, statistical designs, analysis plans, and post-hoc trial analyses produced by the team
• Ensure analytical approaches are scientifically sound, methodologically rigorous, and appropriate for intended use (regulatory, payer, HTA, publication, or internal decision-making)
• Guide the team on complex methodological questions, study design tradeoffs, and interpretation of analytical results
• Review and approve proposed changes to analytical approaches, repository structures, or systems that carry scientific integrity implications

Portfolio & Operational Oversight

• Oversee execution of the analytics portfolio across studies, ensuring alignment with timelines, quality standards, and reporting/KPI requirements
• Monitor study and project status across the team's workstreams; ensure standard repository reports, dashboards, and status updates are accurate and delivered on schedule
• Ensure team adherence to data governance protocols, repository standards, and documentation practices defined by Global Evidence Generation and Data Governance
• Identify and resolve resourcing, timeline, or quality risks across the portfolio before they escalate

Stakeholder Management & Escalation

• Serve as the primary point of escalation for unresolved methodological, data, or resourcing issues raised by the team
• Partner with Global Evidence Generation, RWD Center of Excellence, Data Governance, DD&T, I&A, LOCs, and data owners to align on priorities, resolve cross-functional issues, and clarify requirements
• Escalate high-impact evidence concerns, unclear data limitations, source-selection tradeoffs, and regulatory/payer relevance questions to senior US leadership as appropriate
• Represent the analytics team in cross-functional governance forums, providing updates on portfolio status, risks, and scientific considerations

Qualifications

Experience: >5 years of related work experience; >4 years of experience in the biopharmaceutical industry; experience in evidence generation, RWE / HEOR, clinical operations, study execution, data analysis operations, medical affairs, or scientific communications preferred. Experience managing teams or senior ICs preferred

Technical skills

• Strong understanding of evidence generation studies, post-hoc / SAP analysis workflows, Internal study execution, and study documentation
• Familiarity with RWD / HEOR analyses, trial data, protocol / synopsis workflows, study reporting, and dissemination handoffs
• Ability to manage quality, timelines, documentation, and escalations across analytical and study execution workstreams
• Working knowledge of SAS / R / SQL, evidence repositories, study systems, Veeva, iEnvision, or equivalent platforms preferred
• Strong stakeholder management across Global Evidence Generation, RWD CoE, R&D, DD&T, I&A, Content Factory, and LOCs

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

Languages: Fluent English required; additional languages advantageous

Locations

IND - Bengaluru

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time