Director, AI/ML Strategy and Technology Enablement
Company: Takeda
Location: Boston
Posted on: January 17, 2026
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Job Description:
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that all information I submit in my employment application is true
to the best of my knowledge. Job Description Role Summary Lead the
strategy, platform build-out, and adoption of AI/ML across Research
for global digital transformation effort, making AI agents, models,
and tools a daily, accessible part of wet?lab and dry?lab
scientists’ workflows. Translate AF priorities into a practical,
compliant AI services layer—data foundations, MLOps, agentic
assistants, model governance, and change enablement—that shortens
time from experiment to insight and elevates decision quality
across discovery programs. Objectives / Purpose Define and execute
a multi?year AI/ML roadmap aligned to Research use cases and KPIs.
Establish an AI?ready data foundation (FAIR-by-design) and
scientist?facing AI tools embedded in ELN/LIMS/instrument
workflows. Institutionalize Responsible AI & GxP-aware governance
for production models. Drive adoption through super-user networks,
training, and change management to achieve measurable value and
ROI. Scope / Impact Global Research scope with cross?site
collaboration (US/EU/JP). Direct impact on data-to-decision
latency, assay/analysis reproducibility, and portfolio
productivity. Partner with operations, Computational Sciences &
Data Strategy, IT, function leads, and platform teams to deliver
outcomes at scale. AccountabilitiesStrategy & Roadmap Own
Research’s AI/ML strategy and sequencing (MVP ? scale) across
wet?lab ? dry?lab integration and self?service tools. Align
priorities with Research’s KPIs and portfolio goals; establish and
monitor achievement of success criteria and milestones. Platform,
Data & Integration Guide the development of AI?ready data
foundations (provenance, metadata/ontologies, harmonization) across
ELN/LIMS, instruments, imaging, and omics. Integrate platforms
(e.g., ELN, SDMS & AI Cloud) to liberate, contextualize, and
operationalize lab data for AI/ML. Stand up modern MLOps (CI/CD,
registries, experiment tracking, monitoring) and secure
service/APIs embedded in workflows. Agentic AI & Productization
Design self-service and user-friendly processes for deployment of
AI agents for scientists (literature triage, protocol assist, data
QC, analysis pipelines, code helpers). Guide engineering efforts to
deliver production models (e.g., sequence/structure prediction,
assay QC, outlier detection, multimodal analytics). Adoption &
Change Enablement Lead adoption via super?user networks, training,
and communications; co?own readiness plans with NCSP. Work with
Change Management leads to publish playbooks and guardrails
enabling self?service AI workflows for scientists. Governance, Risk
& Compliance Define and Implement Responsible AI and risk?based
governance (ALCOA, validation mindset, audit trails, XAI,
privacy/PII controls). Impact & Reporting Own measurable impact
(adoption, latency, reproducibility, ROI) and provide transparent
reporting to R&D leadership and key stakeholders.
QualificationsRequired Advanced degree in Computer Science, AI/ML,
Computational Biology/Chemistry, Bioinformatics, or related; or
equivalent industry experience. 10 years in AI/ML for life
sciences; 5 years strategic leadership delivering production AI in
scientific environments. Proven MLOps platform build and delivery
of scientist?facing AI tools embedded in ELN/LIMS/instrument
workflows. Expertise in FAIR data, scientific data
models/ontologies, and integration across wet?lab instruments,
imaging, and omics. Experience with Responsible AI and GxP?adjacent
validation/governance in pharma/biotech R&D. Strong stakeholder
management; ability to translate complex science/data into usable
AI for end users. Preferred Experience working in wet-labs and
knowledge of Research and Development workflows and processes in
either the biologics and/or small molecule fields Agentic AI
systems and LLMs for scientific contexts; multimodal ML
(text/images/sequences/numerical). Knowledge of Research/Pharma Sci
common data models and cloud analytics/HPC integrations. 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: $174,500.00 - $274,230.00 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. U.S. based employees may be
eligible for short-term and/ or long-term incentives. U.S. based
employees may be eligible to participate in medical, dental, vision
insurance, a 401(k) plan and company match, short-term and
long-term disability coverage, basic life insurance, a tuition
reimbursement program, paid volunteer time off, company holidays,
and well-being benefits, among others. U.S. based employees are
also eligible to receive, per calendar year, up to 80 hours of sick
time, and new hires are eligible to accrue up to 120 hours of paid
vacation. 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.
Keywords: Takeda, Leominster , Director, AI/ML Strategy and Technology Enablement, IT / Software / Systems , Boston, Massachusetts
