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Job Description
Role Objectives:
As one of the first Statistics for Study Design and Execution Leads to join the Bengaluru GCM team, this role will establish the statistical capability required to support evidence generation study design and execution, covering statistical analysis plan development, programming, and real-world data analysis.
You will also provide hands-on statistical design and programming support across the evidence generation portfolio, enabling Global Evidence Generation study teams to focus on scientific leadership, endpoint strategy, and final study decisions while GCM delivers analytical execution, statistical planning documentation, and RWD methodology support.
Key Responsibilities :
Initial Capability Build
In the early build phase, work closely with Global Evidence Generation study leads and R&D statistical counterparts to document the scope, standards, tools, templates, and handoff protocols that will govern statistical support activities performed by the GCM going forward
Develop programming standards, analysis templates, SAP shells, output shells, and QC checklists to support consistent and reproducible statistical execution as the team scales to two Leads
Identify gaps in tool access, data system connectivity, or methodology guidance that need to be resolved before statistical activities can be fully transitioned to the GCM and flag these to the AD in a timely manner
Support with development of SOPs and onboarding materials for all statistical programming and RWD analysis activities
Statistical Analysis Planning & Study Design Support
Define appropriate statistical methods for RWD analyses and draft statistical analysis plans in collaboration with the subject matter expert to address evidence generation needs across the drug development life cycle
Lead the implementation of analytic plans, execute analyses for RWE studies using appropriate data sets, as well as standardized methods aligned with GxP for insights, publications, regulatory and payer submissions
Help design interventional and non-interventional (real world) studies, including (where appropriate) sample size calculations and probability of success
Develop and update HTA CTAP (clinical trial analysis plan), post-hoc analysis, and pre-specified analyses
Work on responder analyses using machine learning
Support external controls
Review draft study protocols and synopses for statistical consistency and flag methodological gaps or assumptions requiring retained scientific review and resolution
Document all statistical planning decisions, assumptions, and rationale in study files in line with repository and audit standards
Statistical Programming & Analysis Execution
Generate analysis-ready datasets based on defined use cases and implement analytical methods producing guideline-compliant outputs — including tables, listings, and figures (TLFs) with all data preparation steps documented and traceable throughout
Write, validate, and execute programs in SAS, R, or Python per the Statistical Analysis Plan (SAP); conduct exploratory and ad hoc analyses as requested, clearly documenting assumptions, scope, and limitations for each
Support comparative effectiveness analyses, subgroup analyses, and health economic modeling by providing analytical execution and output production; identify and address common sources of bias in collaboration with the retained statistical SME, testing appropriately for effect modifiers and documenting methodology choices and rationale
Develop and validate statistical models that appropriately account for intercurrent events, competing risks, and…