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.    ACCOUNTABILITIES (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)   Provide scientific leadership across internal and external teams within a matrix environment.   Influence scientific strategy, operating models, and capability development initiatives.   Drive alignment among diverse stakeholders with competing priorities.   Build trust and credibility with scientific leaders, program teams, and external partners.  Decision-making and Autonomy (The capacity and authority to make organizational decisions, autonomy in decision-making, complexity of decisions, impact of decisions, problem-soliving)  Operate independently with broad accountability for quality and effectiveness of external Computational Biology execution.   Make informed decisions regarding analytical approaches, prioritization, quality standards, and risk mitigation.   Provide recommendations that influence program decisions, capability investments, and operational strategy.      Interaction (The span and nature of one’s engagement with others when performing one’s job, internal and external relationships)  Collaborate across Computational Biology, Translational Medicine, Clinical Development, Discovery, Biomarker Sciences, and DD&T functions.   Engage regularly with FSPs, contractors, CROs, academic collaborators, and technology partners.   Communicate complex scientific concepts effectively to technical and non-technical audiences.    Innovation (The required level of scientific knowledge, knowledge sharing, innovation and risk taking)  Drive adoption of scalable analytical approaches and reusable Computational Biology capabilities.   Champion continuous improvement, operational excellence, and knowledge sharing.   Evaluate emerging technologies and identify opportunities to enhance scientific execution and efficiency.      Complexity (Products managed, mix of businesses, internal and/or external business environment, cultural considerations)  TBD/Not applicable  EDUCATION, BEHAVIOURAL COMPETENCIES AND SKILLS:  (List the essential and desirable education and competency requirements to perform the primary responsibilities of the job.  Any minimum requirements should be noted.)  Required  PhD (or MS with significant industry experience) in Computational Biology, Bioinformatics, Systems Biology, Genomics, Data Science or a related discipline.  8+ years of relevant experience in pharmaceutical, biotechnology, CRO, FSP, or related life sciences organizations.  Strong experience applying Computational Biology approaches to drug discovery, translational medicine, biomarker research, precision medicine, or clinical development.  Demonstrated experience guiding complex multi-omics and translational data analyses.  Experience interacting with external scientific partners, contractors, FSPs, CROs, or distributed scientific teams.  Strong matrix leadership and stakeholder-management skills.  Excellent written, verbal, and presentation skills.  Proven ability to operate effectively across geographies, cultures, and time zones.  Preferred  Experience in immunology, gastroenterology, inflammation, rare disease related therapeutic areas.  Experience supporting clinical-stage programs, biomarker strategies, and translational research initiatives.  Experience building reusable analytical workflows, standards, or capability platforms.  Familiarity with cloud-based analytical environments, FAIR data principles, and enterprise data platforms.  Experience mentoring Computational Biologists, Bioinformaticians, Data Scientists, or scientific teams.  Experience operating within global matrix organizations.  Locations IND - Bengaluru - Research and Development Worker Type Employee Worker Sub-Type Regular Time Type Full time