Head, Data & Quantitative Sciences DD&T

Takeda•Boston, MA

4d•$212,000 - $333,190•Hybrid

About The Position

Takeda’s R&D Data, Digital & Technology (DD&T) organization is seeking a senior DD&T leader and strategic partner to R&D Data & Quantitative Sciences (DQS). DQS supports Takeda’s pipeline through portfolio decisions, trial design, analysis for regulatory filings, and safety monitoring. The Head of DQS DD&T sets technology strategy with DQS leadership, plans and delivers a portfolio of technology, data, and AI work through a global team across Cambridge and Takeda’s Innovation Capability Centers, and ensures technology remains reliable, validated, and inspection ready. The role reports to the Head of R&D and Global Medical DD&T and serves on that Leadership Team. The role is accountable for both maintaining pipeline technology readiness and transforming quantitative science in line with Takeda’s AI Forward ambition. This includes applying AI and automation across clinical data and analysis workflows, using simulation and predictive methods to inform development decisions, and building modern data foundations that enable quantitative and computational scientists to develop and deploy models in a governed environment. The position requires technical fluency and creativity in AI and data science, alongside rigor in validation, data integrity, compliance, and audit readiness. The position is hybrid and based in Cambridge, Massachusetts. The stated U.S. base salary range is $212,000 to $333,190. The role is a regular, full-time employee position.

Requirements

Bachelor’s degree required.
At least 12 years of experience in pharmaceutical, biotech, or healthcare R&D technology, including significant leadership of data, digital, or technology delivery with responsibility for teams and budget.
Track record partnering with biometrics, quantitative science, or data science functions and delivering capabilities that improved the speed, quality, and compliance of development and filing work.
Credibility with senior scientific stakeholders and ability to engage substantively on quantitative, computational, and AI problems.
Working knowledge of statistical computing environments, CDISC standards, regulatory submission workflows, modeling and simulation, and safety systems.
Deep knowledge of GxP compliance, computer system validation, data integrity, and inspection readiness.
Demonstrated ability to influence senior leaders and deliver through a highly matrixed global organization, communicating clearly with scientific and executive audiences.

Nice To Haves

Advanced degree in statistics, biostatistics, pharmacometrics, data science, computer science, engineering, or a related quantitative discipline.
Hands-on background in biostatistics, statistical programming, pharmacometrics, or data science within biopharma.
Experience applying AI, machine learning, and automation to regulated clinical and quantitative workflows, including generative and agentic approaches and associated model governance.
Experience delivering through global capability centers or offshore delivery models.

Responsibilities

Serve as the primary DD&T partner and single point of contact for the DQS Leadership Team across strategy, portfolio, platforms, services, and support.
Co-develop a DD&T roadmap with DQS leadership aligned to DQS impact pillars, including quantitative portfolio decisions, fit-for-purpose trial design, speed to lock, submission and access, and predictive, compliant safety risk intelligence.
Represent DQS in DD&T planning, investment prioritization, and technology governance, and represent DD&T in DQS decision forums.
Own the DQS technology portfolio end to end, from demand and prioritization through delivery, adoption, and benefits, ensuring technology supporting development execution and regulatory filings is reliable and ready to meet study, database lock, and submission timelines.
Lead DD&T contributions to DQS priority initiatives, embedding AI and automation into quantitative workflows from clinical data through submission-ready outputs.
Oversee the lifecycle of core DQS technologies, including the statistical computing environment, analysis and reporting pipeline, modeling and simulation platforms, and safety and pharmacovigilance systems.
Ensure applicable DQS systems remain validated and compliant with requirements such as GxP, 21 CFR Part 11, and EU Annex 11; embed quality by design, data integrity, inspection readiness, and AI model governance in regulated workflows.
Represent the technology position in inspections and audits.
Partner across DD&T to use shared Takeda data platforms, AI infrastructure, and governance, and strengthen DQS data foundations.
Enable DQS scientists to develop, validate, and deploy their own models and AI agents by providing appropriate compute, data access, and tooling; maintain awareness of relevant emerging technologies and vendor roadmaps.
Lead, develop, and retain a high-performing global team, establishing clear roles and ways of working across internal teams, ICC capacity, and strategic suppliers.
Manage the DQS DD&T budget, resourcing, and vendor relationships, including contracting, performance, and spend.
Act as a change agent for new ways of working in DQS, support the One DQS agile operating model, and make progress visible through proactive engagement and executive-level reporting.