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Tier-1 brand and metro mid-level role present, but niche RWE/regulatory specialization reduces density.
Heavy regulatory RWE and rare-disease focus makes skills less transferable across industries.
Requires advanced degree, specific registry/RWE regulatory experience, and programming skills, making filters stringent.
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Define and deliver statistical strategies for regulatory-grade analysis of disease registry data supporting rare disease programs.
Lead design, implementation, and validation of advanced statistical models and methods tailored for real-world registry data, ensuring compliance with global regulatory standards.
Collaborate cross-functionally and externally to ensure methodological rigor, data quality, and translate complex analyses into regulatory submissions and briefing documents.
PhD with minimum 4 years relevant industry experience, or Master's degree with minimum 6 years relevant industry experience in statistics, biostatistics, or epidemiology.
Hands-on proficiency in R and/or SAS; understanding of SQL or Python for data engineering and validation.
Experience generating real-world evidence for rare disease programs and contributing to regulatory submissions using registry-based analyses.
Location: Bangalore (Manyata Tech Park) with expectation of minimum three days per week onsite presence.
Experienced statistician skilled in advanced methodologies such as survival analysis, causal inference, propensity score matching, and longitudinal modelling in the context of rare disease registries.
Able to develop and validate novel statistical approaches addressing missing data, data linkage, confounding, and outcome validation to meet regulatory requirements.
Proven ability to influence regulatory strategy and effectively communicate complex statistical results to multi-disciplinary and regulatory audiences.