Business Lead, AI-native End Point Generation

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 Business Lead, AI-native End Point Generation Takeda is transforming how medicines are discovered by building a new Research engine where AI, advanced data platforms, and laboratory automation are embedded directly into how scientists design and discover molecules, run experiments, and make decisions. Our Labs of Tomorrow vision connects computational science, scientific data, and automated experimental workflows into a closed-loop discovery engine that will enable us to design smarter studies, shorten learning cycles, and deliver clearer evidence earlier in discovery with the ultimate goal of discovering differentiated medicines for patients. The Business Lead, AI-native Endpoint Generation is central to realizing this vision. The scientist will be responsible for Takeda's next-generation endpoint generation AI-native software product: owning the scientific vision, customer experience, product strategy, roadmap, adoption, and ultimately the value it creates for our drug discovery. The Business Lead will define and answer what Takeda's interface to the external scientific world should be and how in vivo researchers can better plan and execute studies in a future where AI agents, predictive models, and automated experimentation are the basis of drug discovery, and where every result generated by a partner returns with the protocol, conditions, provenance, and metadata that make it usable, comparable, and ready to inform the next decision. Our ambition is for this product to become the primary environment through which Takeda scientists commission work across our partner network and through which the evidence it produces enters our scientific data foundation complete and contextualized. Purpose The Business Lead, AI-native Endpoint Generation is a foundational leadership role, acting as the as the owner and  of Takeda's Endpoint Generation product family, an integrated family of capabilities spanning the request, execution, and return of experimental data generated in external laboratories and through in vivo research. The role refines the strategic vision for future-state AI-native Endpoint Generation Labs of Tomorrow capabilities and drives its translation into AI-enabled discovery workflows, product direction, adoption, and measurable scientific and business value by working with both relevant internal and external stakeholders. The successful candidate will lead this portfolio as a business owner on the side of the internal customer, combining deep experience in externalized and in vivo data generation with computational, data, and technology fluency to ensure that the products built are science-first, grounded in real discovery and testing workflows, and capable of delivering decision-ready data to the project teams that depend on it. Your customers will be Takeda's in vivo pharmacologists, DMPK and safety scientists, assay and screening scientists, study directors, externalization and outsourcing leads, and the discovery project teams that commission the work. The role carries sufficient technical fluency to provide informed direction on the strategic technology choices underpinning the product family, at the level of intent and trade-off rather than detailed evaluation or execution. This is a unique opportunity for an exceptional leader who can combine deep understanding of externalized and in vivo experimental data generation with strong computational, data, and technology fluency, and who will ensure that the applications developed are scientifically grounded, technically actionable, adoptable by end users, and aligned with Takeda's business priorities. This role operates at the program leadership level, collaborating directly with Takeda's “Labs of Tomorrow” leadership team to shape portfolio priorities, resolve strategic tradeoffs, and ensure future-state endpoint generation capabilities advance from vision to measurable scientific and business impact. The role provides day-to-day direction to the technical leads and development squads working on the Endpoint Generation product family, and is interacting closely with the SME leads. The role will also interface with the other Product Leads to ensure extensibility across the suites of products. Accountabilities Own and refine the strategic vision for the software product suite that enable future-state Endpoint Generation capabilities. Define the future-state endpoint generation journey for AI-native, increasingly automated drug discovery, and translate that vision into the underlying capabilities delivered under a unified mandate and aligned with the overall Research strategy. Deliver against that vision by providing business leadership, partnering with technical leads and development squads on scope, sequencing, and priority, and holding product teams accountable for outcomes, adoption, and measurable scientific and business impact. Define, track, and own KPIs, business value, adoption, and scientific impact across the product family, maintaining the integrated portfolio view that gives Research leadership a consolidated perspective on progress, dependencies, risks, and opportunities. Deeply understand the customer, the re-imagined AI-native workflows, the decisions they make, and unmet needs and represent them throughout development, working closely with the lead Subject Matter Experts to define target scientist experiences and to keep development anchored on discovery science needs and on the priority capabilities that improve how experimental work is commissioned and how evidence returns. Set business priorities and direction across Research, Digital Data & Technology (DD&T), Computational Science, and external build partners, driving the cross-functional alignment needed to resolve risks, dependencies, and blockers across the product family. Work with the broader “Labs of Tomorrow” leadership team to set the digital product roadmap, scope, requirements, and investment priorities, balancing scientific value, strategic importance, and implementation readiness. Provide informed direction on the strategic technology choices underpinning the product family, including platform direction, architecture, and development sequencing, at the level of intent and trade-off rather than detailed evaluation or execution. Identify where AI agents, predictive models, data, and automation can fundamentally redesign how work is placed with partners and how results, protocols, conditions, provenance, and metadata return into Takeda's scientific data foundation, and translate those into opportunities in the products. Plan and drive adoption of delivered capabilities across the discovery project teams, testing functions, and in vivo research groups that depend on them, ensuring that they lead to measurable scientific and business value. Qualifications & Competencies Expected: Ph.D. in pharmacology, biology, drug metabolism and pharmacokinetics, biomedical or veterinary science or related field, with 10+ years of progressively responsible experience in pharmaceutical or biotech R&D. Demonstrated ownership of a product, platform, or capability portfolio end to end, including roadmap, delivery, and adoption. Demonstrated ability to set strategic direction, drive cross-functional alignment, and translate scientific ambition into executable product, workflow, adoption, and value-realization strategies in partnership with technology and product teams. Experience leading portfolio-level initiatives or transformation programs across discovery, computational science, digital, data, product, or technology teams. Hands-on coding experience, including experience coding earlier in career, with sufficient technical fluency to engage credibly with software engineers, computational scientists, data scientists, ML scientists, and technical leads. Demonstrated record of carrying an ambitious vision through to delivered and adopted capability. Strong business judgment, with ability to prioritize initiatives based on scientific value, strategic importance, feasibility, implementation readiness, and measurable impact. Strong experience in discovery-stage experimental data generation, ideally including one or more of in vitro and in vivo pharmacology, drug metabolism and pharmacokinetics, translational and safety assessment, assay operations, externalized research delivery, and/or the management of contract research organizations. Strong fluency in computational, digital, data, automation, and AI/ML concepts as applied to experimental data generation, sufficient to provide informed direction on technology choices and to test technical proposals on business grounds. Experience working across scientific, digital, data, informatics, automation, software, or product teams. Strong stakeholder management skills, including the ability to operate as a single point of accountability across multiple stakeholders and synthesize diverse inputs into clear priorities. Ability to influence without direct authority in a complex matrixed environment. Strong communication skills with the ability to engage senior leaders, scientific stakeholders, product managers, engineers, data scientists, and external partners. Experience directing external technology partners and research service providers from the client side, holding them accountable to scope, timeline, quality, and value while working within their product and delivery models. Preferred experience with scientific software or AI-driven discovery platforms, including ELN/LIMS, study request and order management, in vivo study management, sample and inventory tracking, external data exchange, or assay data platforms. Preferred exposure to one or more of the following: AI/ML-enabled discovery applications, metadata standards, data models, data quality and provenance frameworks for externally generated data, or AI-ready scientific data. ADDITIONAL INFORMATION The position will be based in Cambridge, MA.  This position is currently classified as “hybrid” by Takeda’s Hybrid and Remote Work policy Takeda Compensation and Benefits Summary We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices.  For Location: Boston, MA U.S. Base Salary Range: $212,000.00 - $333,190.00 The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location.  For information about our benefits, please click here. EEO Statement Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law. Locations Boston, MA Worker Type Employee Worker Sub-Type Regular Time Type Full time Job Exempt Yes It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.