Director, Predictive Analytics and AI

Role Summary

Director, Predictive Analytics and AI based in Cambridge, MA. Lead the Data Science team to transform pharmaceutical commercialization using advanced data science and AI, driving innovation in predictive modeling, machine learning, agentic AI, and generative AI to enhance patient identification, HCP targeting, and omnichannel engagement. Mentor a top-tier data science team and accelerate AI/ML solution delivery.

Responsibilities

• Advance Data Science and AI capabilities driving predictive models for Patient finding, HCP Targeting and Prioritization, Next Best Action Engines, and predictive 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 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, leveraging predictive and machine learning models to solve complex business challenges.
• Predictive Modeling & AI Innovation: Design and deploy predictive models and AI/ML algorithms for trialist identification, patient segmentation, NBA, HCP prioritization; create scalable frameworks for AI/ML experimentation and deployment across therapeutic areas.
• Cross-Functional Partnership: Collaborate with cross-functional teams to drive business impact; ensemble multiple third-party patient data sets to enhance coverage and precision.
• Mentor and develop talent: Build a high-performing data science team; promote AI skill development through training, partnerships, and knowledge sharing.
• GenAI and Agentic AI Initiatives: Lead GenAI and Agentic AI initiatives aligned with goals; drive adoption and integration of advanced AI technologies to automate insights generation and support commercial strategies.
• Innovation & Continuous Improvement: Evolve analytical methods and toolsets to meet current and future needs; lead efforts in developing models that provide ongoing insights into execution and industry developments.
• Strategic Consultation & Stakeholder Engagement: Partner with franchise Analytics & Insights, forecasting, and Patient Diagnosis Heads to translate business needs into predictive modeling strategies.
• Vendor & Project Management: Manage vendor relationships for outsourced work; oversee timelines and budgets with project management tools.

Qualifications

• Master‚Äôs or Ph.D. in Computer Science, Data Science, Statistics, Engineering, Economics or related field.
• 10+ years of hands-on AI/ML modeling experience, with at least 5 years in pharmaceutical commercial analytics or healthcare.
• 5+ years of prior management experience.
• Proficiency in AI, with expertise in GenAI and Agentic AI methodologies.
• Strong technical expertise in machine learning, NLP, recommendation systems, and AI personalization use cases.
• Proficient in Python, R, SQL, Databricks; familiarity with AWS, Azure, or GCP.
• Experience with pharma data (IQVIA, Veeva, SP, claims, digital marketing) and strong compliance/privacy understanding.
• Ability to present complex insights to non-technical audiences and mentor others in presentation skills.
• Excellent communication, collaboration, and cross-functional teamwork skills.
• Strong project management and ability to manage multiple projects.
• Demonstrated leadership in a matrix organization and ability to motivate teams.
• Travel: 15% occasional domestic overnight travel may be required.

Skills

• Predictive modeling
• AI/ML algorithms, GenAI, Agentic AI
• HCP targeting and patient segmentation
• NBA and dynamic targeting
• Data governance and compliance
• Cross-functional collaboration
• Data visualization and storytelling
• Project and vendor management

Education

• Master‚Äôs or Ph.D. in related field as listed in Qualifications