Head of Computational Science & Data Strategy, Research

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Job Description

Objective / Purpose:

The Head of Computational Science & Data Strategy is a member of Takeda’s Research Leadership Team (RLT) who serves as the enterprise leader responsible for designing ‘ONE Research’ data strategy with input from the RLT and cross-functional partners, including the Data Sciences Institute (DSI) and Pharmaceutical Sciences (Pharm Sci).  In this capacity, this leader oversees a team of computational scientists and develops and guides the implementation of cutting-edge computational approaches, including Artificial Intelligence (AI) and Machine Learning (ML), to target identification, pathway analysis, biomarker discovery, and the design and optimization of both small and large molecules. Working in strong partnership with Takeda’s Center for External Innovation (CEI), this leader ensures that Takeda Research stays at the cutting-edge of emerging technologies and has access to innovative partnerships and a strong ecosystem of collaborators across academia, medical centers, and biotech.  As more and more of Takeda’s Research data and processes become digitized, this leader provides oversight of data integrity and ensures seamless integration of advanced analytics from target discovery through to relevant clinical data sources, so that high-quality insights are available in ‘real-time’ to support decision making as well as to be applied to dossiers for Health Authorities.

With a bridging seat on the leadership team of DSI, the Head of Computational Science & Data Strategy, Research, ensures a seamless connection with the data infrastructure and governance responsibilities of DSI and its responsibility for enterprise data solutions in partnership with Takeda’s corporate Data & Technology function.  Moreover, this embedding with DSI nurtures fertile Research and Development collaborations that leverage DSI’s excellence in quantitative pharmacology, biostatistics, and big data. 

Under the sponsorship of Pharm Sci leadership, the Research Head of Computational Science & Data Strategy serves to bridge and guide adjacent applications relevant to drug substance and drug product manufacturing, including retrosynthetic AI and computational energetics analyses. With this span from Research to Pharm Sci, this leader plays a visible role guiding a cross-functional computational science strategy, one that is rooted in Research but spans to relevant adjacencies in a highly collaborative and flexible manner.

In summary, Takeda’s Head of Computational Science & Data Strategy ensures that a cutting-edge computational science capability is scaled to the enterprise level so that Takeda Research can effectively harness the power of AI, ML, and digital capabilities to improve the speed and quality of the medicines we seek to deliver to patients.

Accountabilities:

Strategic Vision and Implementation:

• Articulate and implement a compelling vision for the application of cutting-edge computational science approaches across R&D and Pharm Sci that enhance the competitiveness of our pipeline through advanced analytics, AI/ML, and computational chemistry and biology.
• Couple internal and external capabilities to drive groundbreaking innovation in our ability to leverage AI, ML, and computational approaches for sustainable impacts to our R&D projects and functions including Pharm Sci.
• Develop and execute strategies that maximize the value of data science applications (e.g. in AI/ML, Computational Chemistry, and Biology).

Enterprise Leadership and Team Building:

• Build, lead, and inspire a world-class team of data science experts.
• Provide strategic, scientific, and operational leadership to the data sciences team fostering a culture of collaboration and excellence.

Data Governance and Standards:

• Establish and enforce robust data governance and standards across R&D.
• Drive data democratization ensuring all data are structured, accessible, searchable, and useable.
• Collaborate with the R&D stakeholders and external partners to develop and maintain a state-of-the-art data infrastructure.

Portfolio and Resource Management:

• Conduct regular portfolio reviews to assess project progress and optimize resource allocation.
• Prioritize data science initiatives in line with overall R&D strategy and portfolio priorities.
• Allocate resources effectively to support and advance R&D data science initiatives.

Performance Measurement and Reporting:

• Develop and track key performance indicators (KPIs) to measure the impact of data science initiatives.
• Ensure integration of scientific, portfolio, and business information into critical analysis and reporting across the R&D portfolio
• Provide regular updates to senior leadership on progress, key milestones, and strategic recommendations.
• Ensure data integrity and accuracy in all reporting and communication.

Stakeholder Engagement and Representation:

• Serve as the primary liaison for R&D data science, engaging with internal and external stakeholders.
• Raise the visibility of R&D data science within the company and in the broader scientific community.
• Drive iterative review of data and technology strategies to continuously assess effectiveness and identify opportunities for enhancement.

Operational Efficiency and Process Improvement:

• Optimize R&D data science structure and operations dynamically, enhancing capabilities and fostering strong collaborative partnerships.
• Implement new technologies and automation to streamline workflows and drive decision-making.
• Drive continuous improvement in data science methodologies and operational processes.

Education & Competencies(Technical and Behavioral):

• Expected 15 years of management experience in the pharmaceutical industry, with experience leading strategic initiatives and delivering impact at the enterprise level.
• Specialization in digital, with demonstrated proficiency in AI/ML, data sciences, scientific computing, quantitative sciences, and in-silico drug discovery.
• Exceptional leadership and communication skills, with the ability to influence and lead without authority and collaborate effectively with stakeholders at all levels.
• Significant experience in drug discovery and development within the biopharma or biotech sector, from target identification through to initial clinical proof-of-concept.
• A track record of values-driven leadership with a strong commitment to collaborative ways of working that place diversity, equity, and inclusion at the forefront.

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.

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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.

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