Associate Director, Customer Experience Measurements Princeton NJ
Princeton, NJ - USA
Job Summary
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Summary:
This role will lead enterprisewide measurement experimentation and optimization across personal and nonpersonal engagement with a strong focus on media campaign optimization and accountable for establishing standardized measurement frameworks KPI governance and closedloop insight generation that translate engagement and media activity into improved customer experience orchestration performance and business outcomes.
The Associate Director serves as a strategic analytics and insight leader - synthesizing campaign performance data historical learnings experimentation results and decision science outputs (MMx/KDA attribution) to generate actionable intelligence that informs campaign design channel mix sequencing pacing and inflight optimization.
This role plays a critical stewardship function for the Omnichannel Orchestration Engine ensuring execution quality orchestration effectiveness and continuous optimization of both orchestrated and nonorchestrated campaigns. Partnering closely with Brand Analytics Media & Digital Marketing Omnichannel Orchestration/Engine teams CRM Insights Enablement Field Analytics BI&T and Commercial stakeholders the Associate Director delivers dynamic campaign optimization insights and decision frameworks that enable faster learning more efficient media spend and consistent measurement across brands - while operating within a highly regulated healthcare environment.
Responsibilities:
Measurement Strategy KPI Standardization & Governance Lead
Standardized measurement frameworks for customer experience and omnichannel performance across field and digital engagement.
Develop campaign intelligence frameworks that synthesize historical performance decision science outputs (MMx/KDA) and advanced analytics to inform digital campaign planning and optimization at BMS.
Define and govern enterprise KPIs measurement logic metric definitions and reporting standards to ensure consistency and scalability across brands and markets.
Establish closed-loop measurement approaches that evaluate execution quality orchestration effectiveness and cross-channel coordination.
Performance Monitoring & Optimization Insights
Oversee ongoing monitoring of engagement health (e.g. reach frequency engagement opt-outs execution signals) and identify early indicators of deviation or opportunity.
Translate performance trends into actionable optimization recommendations for orchestration logic channel utilization workload balance and pacing.
Develop and maintain executive-ready dashboards and narratives that connect engagement activity to customer experience and business outcomes.
Experimentation & Incrementality (Test & Learn)
Design and operationalize test-and-learn approaches (e.g. A/B tests lift studies incrementality experiments matched control designs) to assess impact and scalability of innovations.
Define success metrics measurement windows and analytical methods; ensure results are translated into decisions on what to scale refine or stop.
Partner with media CRM and activation teams to embed experimentation learnings into ongoing and future campaign execution
Omnichannel Orchestration Engine Measurement
Lead standardized measurement and optimization frameworks for the Omnichannel Orchestration Engine across both personal and non-personal channels enabling always on closed loop measurement of execution quality orchestration effectiveness and cross channel coordination.
Oversee continuous monitoring of omnichannel execution healthincluding reach frequency engagement optouts and recommendation execution signalsand assess performance trends and early indicators of deviation.
Translate insights into actionable optimization recommendations to improve channel mix sequencing pacing workload balance and content delivery while providing analytical feedback to Omnichannel Engine Salesforce and Field Excellence partners.
Deliver dynamic insights and decision frameworks that enable faster learning more efficient media spend and consistent measurement across brands.
Content Message & Personalization Measurement
Lead measurement of content and message performance (e.g. adoption freshness affinity fatigue segment/channel suitability).
Enable evaluation of AI-driven personalization/NBA strategies and their impact on customer experience and downstream outcomes.
Provide recommendations to optimize content mix creative rotation channel fit and sequencing.
Stakeholder Partnership & Enablement
Serve as a trusted analytics advisor across Marketing Omnichannel Strategy Field Excellence and Commercial stakeholders.
Facilitate regular insight feedback loops to refine targeting orchestration pacing and engagement strategy.
Drive adoption of measurement standards and best practices through training documentation playbooks and stakeholder enablement.
Innovation AI & Responsible Insight Enablement
Partner with data science and other partners to pilot and scale advanced analytics capabilities (e.g. clustering/embeddings pattern detection content analysis).
Enable responsible use of LLMs for insight generation and enablement (e.g. summarization classification explanation) ensuring governance explainability and compliance.
Qualifications:
Bachelors degree in Computer Science Data Science Analytics Statistics Economics or related quantitative field is required
Minimum 6 years of experience in omnichannel engagement measurement advanced analytics or commercial insights within the pharmaceutical industry.
Strong understanding of HCP and/or patient journeys including channel interactions sequencing pacing and message effectiveness.
Demonstrated experience designing measurement frameworks KPI standardization reporting requirements and analytics governance.
Expertise in impact measurement methods including attribution experimentation/incrementality and causal inference approaches.
Proven ability to translate analytics into clear actionable recommendations and influence cross-functional stakeholders.
Proficiency with Python or R for analysis/modeling and working with modern data environments.
Preferred Experience
applying machine learning techniques including embedding based clustering to identify high value channel and journey patterns content effectiveness message fatigue and under or oversaturated channels.
Practical experience leveraging large language models (LLMs) as an insight and enablement layer on top of core analytics including prompt design for classification summarization explanation of analytical results and insight generation.
Ability to validate AI generated insights with analytical rigor and business logic ensuring explainability trust and compliance. Proficiency in SQL and machine learning modeling in Python (e.g. pandas NumPy stats models causal libraries).
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If you come across a role that intrigues you but doesnt perfectly line up with your resume we encourage you to apply anyway. You could be one step away from work that will transform your life and career.
Compensation Overview:
Princeton - NJ - US: $167540 - $203013
Required Experience:
Director
About Company
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