Associate Director, Predictive Analytics

Associate Director, Predictive Analytics – Cambridge, MA

We are seeking a hands‑on innovative seasoned Data Science professional to lead advanced analytics for Takeda’s US GI Franchise. In this strategic, hands‑on role, you will drive innovation in predictive modeling, machine learning, and AI technologies to enhance patient identification, HCP targeting, and omnichannel engagement.

• Advanced data science capabilities driving predictive models in areas including patient finding, HCP targeting & prioritization, next‑best action engines, and predictive patient & customer segmentation.
• Advanced predictive analytics for the US GI franchise, including new product launches or indications.
• Partner with BUs, BU Analytics & Insights, Marketing, Sales Ops, Data CoEs, etc., to define use cases and integrate predictive model‑driven decisioning into business decisions.
• Develop and execute a future‑oriented data science strategy for commercialization, focusing on leveraging predictive and machine learning models to solve complex business challenges.
• 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, and support targeted HCP engagements.
• Leverage/create scalable, reusable AI/ML frameworks for learning experimentation and deployment.
• Collaborate as a key thought partner with cross‑functional teams—Business Units, Brand Insights & Analytics, Marketing & Sales Operations, Patient Services, and Medical Affairs—to drive business impact.
• Mentor a high‑performing team of data scientists, promoting continuous learning and adoption of emerging AI techniques.
• Continuously evolve analytical methods, platforms, standards, and toolsets to meet current and future business needs.
• Act as a trusted thought partner to franchise Analytics & Insights, forecasting, and Patient Diagnosis Heads, leading data‑science–driven discussions.
• Drive the adoption and integration of advanced AI technologies (GenAI, Agentic AI) to enhance analytics capabilities and automate insights generation.
• Manage relationships with vendor partners for outsourced project work and ensure high‑quality, timely deliverables.

• BS/BA in a quantitative field (e.g., Statistics, Data Science) with 8+ years of relevant experience in the pharmaceutical industry; advanced degree (MS/MA) preferred.
• 5+ years of hands‑on AI/ML modeling experience, with at least 3 years in pharmaceutical commercial analytics.
• Strong technical expertise in machine learning, NLP, recommendation systems, and personalization use cases.
• Proficient in data science tools and languages such as Python, R, SQL, Databricks, and familiar with cloud platforms (AWS, Azure, GCP).
• Experience with pharma data (IQVIA, Veeva, SP, claims, digital marketing) and strong understanding of compliance and privacy considerations.
• Expert in delivering persuasive presentations, conveying complex data science insights to non‑technical audiences, and mentoring others.
• Excellent communication and collaboration skills, capable of working effectively cross‑functionally.
• Strong project management skills, managing multiple projects simultaneously.
• Demonstrated leadership in a matrix organization, motivating and inspiring team members to high‑performance levels.
• Flexibility to adapt to changing business needs and evolving technology landscapes.

Location:

Cambridge, MA (Kendall Square) – hybrid work model.

U.S. Base Salary Range: $ - $. Bonus, medical, dental, vision, 401(k) with match, disability, life insurance, tuition reimbursement, volunteer time off, holidays, wellness benefits, sick time (80 hours annually), paid vacation (up to 120 hours for new hires). U.S. employees may also receive short‑term and/or long‑term incentives.

Takeda is proud of 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.