Director, Advanced Analytics and Data Science

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Job Description

The Director, Advanced Analytics and Data Science is responsible for performing complex data research and analysis to support business operations. By creating data mining architectures, statistical reporting, and data analysis methodologies, this role helps identify trends in large data sets and informs business decisions.

OBJECTIVES/PURPOSE

• Define and lead advanced analytics strategy that delivers actionable insights and AI/ML-driven personalization to drive Oncology US objectives. 

• Oversee development and application of marketing mix modeling, ROI analysis, and omnichannel optimization to maximize promotional effectiveness and customer engagement. 

• Design and implement scalable AI/ML predictive analytics solutions (e.g., next-best-action, next-best-channel, advanced targeting) for HCP, patient, payer, and medical engagements. 

• Enable data-driven decision-making through robust, complaint, and production-ready models embedded in business workflows through close collaboration with cross-functional partners 

• Foster a culture of high-performing, collaborative analytics that partners effectively with commercial, medical, digital, DD&T, and finance teams and adeptly influences without authority 

ACCOUNTABILITIES

• Define and lead the advanced analytics strategy to align with Oncology BU goals, balancing short-term impact with long-term capability-building (inclusive of preparing and evaluating a dedicated offshore analytics team) 

• Design and deliver marketing mix models, ROI analysis, and omnichannel optimization to inform investment decisions and maximize customer engagement effectiveness. 

• Design and operationalize advanced AI/ML solutions (e.g., next-best-action, segmentation, targeting) to enable scalable, compliant personalization across HCP, patient, and payer engagements. 

• Drive experimentation with novel data sources and advanced modeling approaches, including GenAI, to enhance precision, relevance, and self-serve analytics capabilities. 

• Establish and monitor meaningful KPIs and ROI metrics to evaluate and continuously improve the impact of AI/ML initiatives. 

• Translate complex analytics and model outputs into clear, actionable insights and recommendations that enable senior leadership decision-making and drive commercial excellence. 

• Foster strong cross-functional alignment and collaboration by partnering with marketing, digital, DD&T, finance, and medical teams to embed analytics-driven decision-making. 

• Build, mentor, and lead a high-performing, inclusive analytics team—comprising indirec