Associate Director, Data Science Lead

Role Summary

The Associate Director, Data Science Lead drives advanced modeling solutions to inform strategic business decisions across Marketing, Sales, and Access. Leads high-impact data science initiatives including marketing optimization, patient-level predictive analytics, ML-based personalization, and field force effectiveness strategies. Acts as a hands-on contributor and thought partner to commercial leadership, ensuring data science outputs are actionable, accurate, scalable, and aligned with brand priorities.

Responsibilities

• Execute long-term data science and AI vision aligned with enterprise roadmaps and commercial priorities.
• Lead end-to-end development, deployment, and scaling of data science solutions (predictive models, clustering, segmentation, optimization, NLP/LLMs) to address complex commercial challenges and extract insights from unstructured data.
• Partner with insights and marketing teams, applying rigorous data science methods and agile practices.
• Incorporate adopter feedback to continuously refine model quality and performance.
• Serve as primary data science partner for U.S. commercial brand teams, translating objectives into analytical frameworks that drive measurable impact.
• Guide stakeholders through insight interpretation and activation, integrating outputs into workflows and decision-making.
• Provide technical expertise and thought leadership on analytical tools, reusable frameworks, and proprietary data products.
• Promote analytical rigor, responsible experimentation, and model governance across the analytics organization.
• Collaborate with a high-performing data science team and with IT to develop ML Ops environments and productized solutions.
• Design and operationalize Next Best Action (NBA) strategies to optimize field force effectiveness and omnichannel engagement.
• Develop and scale Patient 360 models and predictive targeting algorithms to support AI-driven lead generation and high-value outreach.
• Lead measurement and ROI optimization through marketing/media mix modeling and budget allocation using relevant data sources.
• Manage relationships with external analytics partners, ensuring alignment with internal teams for scalable, secure delivery.

Qualifications

• Minimum 7 years of hands-on analytics or data science experience, including at least 4 years leading data science projects or teams.
• Strong command of statistical modeling, supervised and unsupervised learning, A/B testing, and time-series forecasting.
• Experience in marketing mix, portfolio optimization, and Gen AI product design; commercial deployment in pharma/biotech/healthcare preferred.
• Proficient in Python, R, SQL, and Snowflake; experience with Power BI or Tableau.
• Proven track record in NBAs, marketing optimization models, and omnichannel analytics.
• Experience with APLD, PlanTrak, specialty pharmacy, or claims datasets.
• Strong communication and influencing skills; comfortable presenting to senior stakeholders and cross-functional teams.

Education

• Preferred: Master’s degree in data science, Statistics, Engineering, Computer Science, Business Analytics, or related field.

Additional Requirements

• No explicit travel or physical demands specified as essential in the provided description.