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Takeda Pharmaceutical
Head of Biotherapeutics Data and Modeling Applications
Career Insights for Data Scientist
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Based on Massachusetts data
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What they do
A Data Scientist utilizes skills and experience to systematically answer questions using data to provide actionable recommendations. Commonly utilizes advanced statistical analysis and machine learning techniques. Common responsibilities also include data cleaning and data management.
$116,058 / year median in Massachusetts
+20% projected growth
Job Description
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Job Description Job Description:
Head of Biotherapeutics Data and Modeling Applications (Director) About the role: You will lead the Biotherapeutics Data and Modeling function, responsible for defining and delivering data, digital and modeling capabilities that enable reliable, high‑quality biotherapeutic development and manufacturing. This role combines leadership of data and modeling teams with responsibility for identifying and deploying data platforms and analytics tools in close collaboration with the digital, data and technology organization (DD&T). You will drive a modeling strategy that produces robust and predictive models of internal platform processes, ensure alignment with quality and regulatory expectations, and bring external industry insights into the technology roadmap to keep our capabilities current and competitive.How you will contribute:
- You will lead and grow a team of data engineers and modelers, setting strategy, priorities and measures of success.
- Identify and deploy data and digital platforms and tools in partnership with the digital, data and technology organization (DD&T) to support process development and scale‑up to manufacturing.
- Drive the modeling strategy to establish robust, validated predictive models of our internal platform processes, combining mechanistic modeling, statistical modeling and machine learning where appropriate.
- Translate model outputs into operational decisions and control strategies that improve quality, yield, cost, safety, reliability and performance.
- Partner with process development, operations, quality, and information technology to ensure models and platforms meet validation and data integrity requirements.
- Align and influence data governance, architecture and best practices for data capture, lineage, storage, and access to enable reproducible models and analytics in collaboration with peers in PharmSci.
- Maintain an active external presence and professional network to monitor industry‑leading data and digital trends, evaluate new technologies, and incorporate relevant insights into the technology roadmap.
- Manage vendor selection, partnerships and external collaborations in collaboration with partners in PharmSci and
R D DD&T
for data engineering and modeling tools.- Provide strategic oversight of budgets, schedules and major initiatives while mentoring team members.
Skills and qualifications:
- Minimum of ten years of relevant experience in biotherapeutics, bioprocess development, data science, computational modeling or related fields, including at least five years in a leadership role.
- Advanced degree in engineering, computational biology, data science, statistics, or a closely related discipline; doctoral degree preferred but not required.
- Demonstrated experience identifying and deploying enterprise data platforms and digital tools that support biologics development.
- Proven track record building and validating predictive models for process performance using mechanistic approaches, statistical methods and machine learning, and translating models into operational controls.
- Strong understanding of regulatory expectations and quality systems for data and models in regulated environments, including data integrity and model validation practices.
- Hands‑on knowledge of data engineering and cloud technologies, data architecture, database systems, and modern tooling for model development and deployment.
- Experience collaborating across process development, quality and IT teams to implement data‑driven solutions.
- Excellent interpersonal and communication skills, including presenting technical concepts to non‑technical audiences and representing the organization externally.
- Experience managing vendors and external partnerships, and a track record of building professional networks and engaging with academic or industry collaborators.
- Familiarity with process improvement methodologies such as Six Sigma or Lean is desirable.