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

Join Takeda as a Director, Predictive Analytics and AI out of our Cambridge, MA office. We are seeking a visionary Director to lead our Data Science team, transforming pharmaceutical commercialization with advanced data science and AI. In this strategic, hands-on role, you will drive innovation in predictive modeling, machine learning models, agentic AI, and generative AI technologies to enhance patient identification, HCP targeting, and omnichannel engagement. You will empower a top-tier data science team through mentorship and development, accelerating cutting-edge AI/ML solution delivery.

This position requires strong technical expertise, business acumen, and creative strategy to translate sophisticated analytics into actionable business solutions, delivering commercial excellence in areas such as trialist identification, patient segmentation, next-best-action (NBA), target prioritization dynamic targeting, and execution of AI/ML strategies to enable scalable personalization across HCP and patient stakeholders.

The leader brings a consultative approach to partnering with stakeholders to identify new business opportunities, develop advanced analytic insights informing strategies, and drive AI/ML & data driven decision making for business growth. You will collaborate with internal and external stakeholders to ensure models can be deployed in compliant, production-ready environments with clear plans to measure effectiveness.

How you will contribute:

• Advance Data Science and AI capabilities driving the utilization of predictive models in areas including Patient finding, HCP Targeting and Prioritization, Next Best Action Engines, predictive secondary data driven Patient and predictive Customer Segmentations.
• Advance Predictive Analytics for US. GI, NS, PDT, and Rare Disease Franchises, including new product launches or indications.
• Partner with BUs, BU Analytics & Insights, Marketing and Sales Ops, Data CoEs etc.to define use cases and integrate predictive model-driven decisioning into business decisions.
• Strategic Leadership: Develop and execute a future-oriented data science strategy for commercialization, focusing on leveraging predictive and machine learning models to solve complex business challenges.
• Predictive Modeling & AI Innovation: Design and deploy predictive models—including logistic regression, ensemble methods, and other machine learning algorithms—for key applications such as trialist identification, patient segmentation, next-best-action (NBA), and HCP target prioritization. Lead
  the development of AI/ML algorithms to predict patient events, identify undiagnosed / misdiagnosed patients to drive targeted HCP engagements. Create scalable, reusable frameworks for AI and machine learning experimentation and deployment across multiple therapeutic areas.
• Cross-Functional Partnership: Collaborate as a key thought partner with cross-functional teams—including Business Units, Brand Insights & Analytics, Marketing & Sales Operations, Patient Services, and Medical Affairs—to drive business impact. Develop creative strategies to ensemble multiple third-party patient data sets, enhancing coverage and precision in patient identification and predictive
  segmentations.
• Mentor and develop talent: Cultivate a high-performing team of data scientists by promoting continuous learning and encouraging the adoption of emerging AI techniques, ensuring a culture of innovation and excellence. Promote ongoing AI skill development through hands-on training, external partnerships, and internal knowledge sharing.
• GenAI and Agentic AI Initiatives: Establish and lead GenAI and Agentic AI initiatives that are strategically aligned with CA&I goals. Drive the adoption and integration of advanced AI technologies to enhance analytics capabilities, automate insights generation, and support innovative commercial strategies.
• Innovation & Continuous Improvement: Continually evolve analytical methods, platforms, standards, and toolsets to meet current and future business needs. Lead Data Science team efforts in developing advanced analytic and AI models providing continuous insights into execution optimization, and industry developments.
• Strate