Associate Director, Predictive Analytics
Takeda
June 29, 2026
Remote friendly (Cambridge, MA)
United States
$154,400 - $242,550 USD yearly
IT
Associate Director, Predictive Analytics (Cambridge, MA) — hands-on Data Science leader for Takeda’s US GI Franchise.
Responsibilities:
- Drive advanced predictive modeling and AI/ML for patient identification, HCP targeting/prioritization, omnichannel engagement, trialist identification, and patient segmentation.
- Design and deploy predictive models (e.g., logistic regression, ensemble methods, other ML algorithms) for next-best-action (NBA) and target prioritization/dynamic targeting.
- Develop AI/ML algorithms to predict patient events and identify undiagnosed/misdiagnosed patients; build scalable, reusable AI/ML frameworks for experimentation and deployment.
- Partner with Business Units, Analytics & Insights, Marketing/Sales Ops, Patient Services, and Medical Affairs to define use cases and integrate predictive decisioning into business decisions.
- Mentor data scientists, promote continuous learning, and lead continuous improvement of methods/tools/platforms.
- Manage vendor relationships and oversee project timelines and budgets.
Qualifications (Minimum/Preferred):
- BS/BA in a quantitative field with 8+ years pharmaceutical industry experience; MS/MA preferred.
- 5+ years hands-on AI/ML modeling; 3+ years in pharmaceutical commercial analytics.
- Expertise in machine learning, NLP, recommendation systems, and personalization.
- Proficient in Python, R, SQL, Databricks; familiarity with AWS/Azure/GCP.
- Pharma data experience (e.g., IQVIA, Veeva, SP, claims, digital marketing) and strong compliance/privacy understanding.
- Excellent communication, cross-functional collaboration, presentation, and project management; leadership in matrix organizations.
Skills:
- Presentation to non-technical audiences; persuasive storytelling of DS insights; mentoring.
Application instructions:
- Submit application via the “Apply” button.
Responsibilities:
- Drive advanced predictive modeling and AI/ML for patient identification, HCP targeting/prioritization, omnichannel engagement, trialist identification, and patient segmentation.
- Design and deploy predictive models (e.g., logistic regression, ensemble methods, other ML algorithms) for next-best-action (NBA) and target prioritization/dynamic targeting.
- Develop AI/ML algorithms to predict patient events and identify undiagnosed/misdiagnosed patients; build scalable, reusable AI/ML frameworks for experimentation and deployment.
- Partner with Business Units, Analytics & Insights, Marketing/Sales Ops, Patient Services, and Medical Affairs to define use cases and integrate predictive decisioning into business decisions.
- Mentor data scientists, promote continuous learning, and lead continuous improvement of methods/tools/platforms.
- Manage vendor relationships and oversee project timelines and budgets.
Qualifications (Minimum/Preferred):
- BS/BA in a quantitative field with 8+ years pharmaceutical industry experience; MS/MA preferred.
- 5+ years hands-on AI/ML modeling; 3+ years in pharmaceutical commercial analytics.
- Expertise in machine learning, NLP, recommendation systems, and personalization.
- Proficient in Python, R, SQL, Databricks; familiarity with AWS/Azure/GCP.
- Pharma data experience (e.g., IQVIA, Veeva, SP, claims, digital marketing) and strong compliance/privacy understanding.
- Excellent communication, cross-functional collaboration, presentation, and project management; leadership in matrix organizations.
Skills:
- Presentation to non-technical audiences; persuasive storytelling of DS insights; mentoring.
Application instructions:
- Submit application via the “Apply” button.