Head of Analytical Data & Statistics

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 Are you looking for a patient-focused, innovation-driven company that will inspire you and empower you to shine? Join us as a Head of Analytical Data & Statistics in our Cambridge office. At Takeda, we are transforming the pharmaceutical industry through our R&D-driven market leadership and being a values-led company. To do this, we empower our people to realize their potential through life-changing work. Certified as a Global Top Employer, we offer stimulating careers, encourage innovation, and strive for excellence in everything we do. We foster an inclusive, collaborative workplace, in which our global teams are united by an unwavering commitment to deliver Better Health and a Brighter Future to people around the world. Here, you will be a vital contributor to our inspiring, bold mission. OBJECTIVES/PURPOSE : Establish and continuously improve statistical and analytical standards, methods, and governance for the organization. Ensure robust data architecture, collection, validation, and quality control processes to maintain data integrity and traceability. Embed analytics into study/assay design and milestone decisions through close partnership with cross-functional teams. Deliver clear, actionable insights and visual reporting that inform program strategy, prioritization, and resource allocation. Drive adoption of modern analytical tools and data automation to improve speed, reproducibility, and scalability (e.g., AI-assisted generation and modelling where appropriate). Maintain compliance with applicable regulations and industry best practices for statistical analysis and data management. Develop team capability through hiring, coaching, training, and performance development. ACCOUNTABILITIES: Lead and manage the Analytical Data and Statistics team to deliver high-quality data analysis and reporting. Develop and implement advanced statistical methods and analytical frameworks to support biotechnology research and development. Collaborate with cross-functional teams to integrate data analytics into experimental design and decision-making processes. Oversee data collection and architecture, validation, and quality control procedures to ensure data integrity and compliance with regulatory requirements. Drive innovation in data analytics by evaluating and adopting new tools, technologies, and methodologies. Present analytical findings and insights to senior leadership to guide strategic planning and project prioritization. Ensure compliance with industry standards, guidelines, and best practices in statistical analysis and data management. Mentor and train team members to build expertise in statistical techniques and data analytics. DIMENSIONS AND ASPECTS: Technical/Functional (Line) Expertise: Deep expertise in applied statistics for Analytical Development (e.g., DoE, regression/multivariate methods, variance components, measurement system analysis, stability trending, and comparability assessments). Strong command of analytical data types and workflows (chromatography, electrophoresis, mass spectrometry, potency/bioassays) and the key sources of variability that drive method performance. Experience defining and governing data standards, statistical analysis plans, and fit-for-purpose acceptance criteria for method development, qualification/validation, and lifecycle management. Proficiency with modern analytics tooling (R/Python/SAS or equivalent), reproducible workflows (version control, code review), and visualization/dashboarding practices. Understanding of GxP-relevant data integrity and compliance expectations (ALCOA+, audit trails, validation of computerized systems) and how they apply to analytical data and reporting. Capability to translate complex analyses into decision-ready narratives for technical and non-technical stakeholders; strong scientific judgment on uncertainty and risk. Familiarity with analytical informatics ecosystems (LIMS/ELN/CDS and data lakes) and data integration/automation approaches to enable scalable insights. Leadership: Sets vision and strategy for how analytical data and statistics enable portfolio decisions; aligns priorities, resourcing, and roadmap to AD and enterprise objectives. Leads, coaches, and develops a multidisciplinary team; sets expectations, builds capability, and fosters a culture of quality and continuous improvement. Influences cross-functionally to embed data-driven ways of working; establishes governance/operating cadence, leads change adoption for standards and tools, and communicates complex analyses clearly with risk and uncertainty framing. Decision-making and Autonomy: Owns prioritization of the Analytical Data & Statistics portfolio and allocation of team capacity; sets delivery commitments, timelines, and quality expectations. Defines and approves statistical approaches, analysis plans, and reporting standards for AD studies and method lifecycle activities; serves as the escalation point for complex technical/statistical issues. Makes decisions on data governance (data standards, metadata, access/retention, and validation requirements) and ensures alignment with GxP expectations and internal policies. Recommends go/no-go and risk-based options at key program milestones by translating uncertainty into clear decision trade-offs (speed, cost, quality, and compliance). Selects and champions analytics tools and digital solutions within delegated authority; escalates investments with material budget, compliance, or enterprise architecture impact. Makes decisions on data governance (data standards, metadata, access/retention, and validation requirements) and ensures alignment with GxP expectations and internal policies. Recommends go/no-go and risk-based options at key program milestones by translating uncertainty into clear decision trade-offs (speed, cost, quality, and compliance). Selects and champions analytics tools and digital solutions within delegated authority; escalates investments with material budget, compliance, or enterprise architecture impact. Interaction: Internal AD teams: Daily partnership with Analytical Development functional leads and project teams to frame analytical questions, shape study/assay designs, and interpret results for milestone decisions. Internal Quality/Regulatory: Routine engagement with QA/Quality Systems and Regulatory CMC/Technical Writing to ensure data integrity, inspection readiness, and submission-ready statistical rationales and presentations. Internal & External Digital/Operations: Close collaboration with IT/Lab Informatics/data platform teams (LIMS/ELN/CDS, data lakes) plus MSAT/Manufacturing and DD&T to enable validated solutions. Innovation: Identifies and