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Metro Bengaluru location, mid-level Manager title, and reputable pharma brand increase competition despite niche clinical specialization.
Strong requirement for clinical trial, CDISC, and regulatory expertise limits transferability across industries.
Mandated CDISC, regulatory, advanced statistics, and reproducible workflows create stringent shortlisting filters.
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Manage clinical data science activities for assigned clinical development studies or workstreams, ensuring high-quality, timely delivery of analysis-ready data, quantitative analyses, and insights.
Support clinical study objectives by applying statistical, data science, AI/ML, and advanced analytics methods including exploratory analyses, data visualization, and interpretation using diverse data sources (clinical trial, biomarker, real-world, etc.).
Drive adoption of automation, reusable analytical workflows, and maintain regulatory compliance and scientific rigor in data preparation and analysis processes.
PhD in statistics, biostatistics, data science, epidemiology, biomedical engineering, computer science, quantitative sciences, or related field; or MS with 3+ years relevant experience.
Experience in pharmaceutical, biotechnology, healthcare research, or another regulated clinical development environment applying quantitative analytics and data science to clinical data.
Proficiency in R and/or Python, working knowledge of SAS and SQL, plus understanding of CDISC standards (SDTM, ADaM, Define-XML) for clinical trial data.
Experience with clinical trial data and at least one additional complex data type (biomarker, real-world, imaging, digital health, or other high-dimensional data).
Operational focus on delivering reproducible, traceable, automated, and high-quality analytical workflows supporting clinical decision making within cross-functional study teams.
Strong foundation in statistics and applied clinical data science with hands-on experience in advanced analytics including AI/ML in regulated environments.
Effective communicator of quantitative insights to interdisciplinary stakeholders with ability to identify risks and support regulatory and scientific standards adherence.