Associate Director, Computational Biology

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 Takeda’s 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 OBJECTIVES/ PURPOSE (3-4 bullets) We have an exciting opportunity for an Associate Director / Director, Computational Biology Scientific Operations & Capability Lead to join the Computational Biology team within the Gastrointestinal & Inflammation Therapeutic Area Unit (GI²-TAU). We are looking for: A scientific leader who will play a pivotal role in expanding Computational Biology capabilities and scientific impact across GI² programs through high-quality external scientific execution, reusable analytical capabilities, and operational excellence. An expert in computational biology and translational bioinformatics with deep experience in multi-omics analysis, biomarker research, and AI/ML-enabled analytical approaches, capable of guiding and critically evaluating complex scientific analyses. A strategic collaborator who will partner with clinical development, translational medicine, discovery, and DD&T teams to ensure externally supported Computational Biology activities remain aligned with program priorities and portfolio needs. A capability builder and innovator who will establish scalable workflows, scientific standards, and best practices that improve consistency, quality, and reproducibility across Computational Biology activities. A scientific operations leader who will serve as the primary interface between the Boston-based Computational Biology team and India-based FSPs, contractors, and external scientific partners, reducing communication, coordination, and oversight burden while strengthening execution quality across the network. A CCOUNTABILITIES (Describe the primary duties and responsibilities of the job . Include only the essential functions of the job. Approximately 5 – 10 bulleted task statements should be identified ). Scientific Operations & External Execution Serve as the primary scientific interface between the Boston-based Computational Biology team and India-based FSPs, contractors, and external partners. Translate GI² scientific priorities into clear analytical plans, deliverables, and quality expectations. Oversee externally supported Computational Biology activities and reduce coordination and oversight burden on Boston-based scientists. Scientific Leadership & Quality Provide scientific leadership and oversight for Computational Biology analyses, ensuring outputs are rigorous, reproducible, and decision-ready . Apply expertise in computational biology, multi-omics, biomarkers, and translational research to guide analysis and interpretation. Capability Development Build reusable Computational Biology workflows, standards, and best practices that can be applied across programs and disease areas. Advance scalable analytical capabilities through partnerships with Computational Biology, Digital , DD&T, and Data Science teams. Program Support & Collaboration Maintain targeted engagement with priority programs to ensure external execution remains aligned with scientific and portfolio priorities. Support program teams with insights related to biomarkers, disease biology, patient stratification, and multi-omics analysis. Foster a culture of scientific excellence, innovation, collaboration, and continuous improvement across internal and external teams. Technical/Functional (Line) Expertise ( Breadth and depth of knowledge, application and complexity of technical knowledge ) Deep expertise in Computational Biology, Bioinformatics, Systems Biology, Translational Bioinformatics, or related disciplines. Strong background in multi-omics analysis, biomarker discovery, patient stratification, and translational data analysis. Experience applying advanced analytical approaches, including AI/ML methods, to support decision-making. Ability to review, challenge, and guide complex scientific analyses and biological interpretations. Strong understanding of reproducible research practices, data quality standards, and analytical governance. Leadership (Vision, strategy and business alignment, people management, communication, influencing others, managing change) </div