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Associate Director, Clinical Data Scientist (Bengaluru)

2028 Takeda Innovations India · Bangalore

📅 20/08/2026
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By clicking the Apply button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takedas Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge. Job Description Job Description - Serve as an Associate Director-level clinical data science leader within Data & Quantitative Sciences, translating complex clinical, biomarker, and external data into actionable evidence that informs clinical development decisions. - Lead fit-for-purpose statistical, data science, and advanced analytics approaches across assigned studies, assets, or specialty areas, including exploratory analysis, predictive modeling, simulation, and integrated data review. - Partner cross-functionally with Clinical, Clinical Pharmacology, PSPV, Clinical Data Management, Translational Sciences, Regulatory, Clinical Operations, and external partners to ensure high-quality, traceable, analysis and submission-ready data and decision-ready insights. - Advance up-to-date ways of working by applying AI/ML, automation, reusable analytics workflows, and governed data standards while maintaining scientific rigor, regulatory awareness, and patient-focused decision making. Accountabilities: - Lead clinical data science strategy and delivery for one or more studies, assets, or capability areas, ensuring alignment with development objectives, timelines, quality expectations, and stakeholder needs. - Design and/or execute quantitative analyses using clinical trial data, biomarkers, real-world data, external data, and other relevant sources to generate interpretable insights for study teams and governance forums. - Apply appropriate statistical, machine learning, simulation, and visualization methods to support patient-level prediction, endpoint interpretation, risk assessment, scenario planning, and evidence generation. - .
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