Business Lead, AI-native End Point Generation
Listed on 2026-09-10
-
Engineering
AI Business & Operations, Research Scientist, AI Engineer (Applied/Software)
For
Location:
Boston, MA
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U.S. Base Salary Range: $ - $
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.
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EEO StatementTakeda 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.
LocationsBoston, MA
Worker TypeEmployee
Worker Sub-TypeRegular
Time TypeFull time
Job ExemptYes
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.
Job DescriptionBusiness 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 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…
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