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Tier-1 brand and metro location increase applicants, but niche MMx and agentic AI requirements limit the pool.
Role requires deep pharmaceutical commercial analytics and MMx domain knowledge, limiting cross-industry transferability.
Explicit 10+ years, mandatory pharma MMx/LLM operationalization and regulated-domain requirements create strict filters.
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Lead design, building, validation, and deployment of Marketing Mix Models (MMx) and advanced econometric/AI models to optimize US pharmaceutical commercialization.
Develop and operationalize AI-driven decision systems including agentic AI frameworks for commercial analytics, ensuring model trust, interpretability, and integration into brand and commercialization workflows.
Mentor and train junior analysts, establish modeling standards, and create reusable frameworks to enhance team capabilities and analytics impact across commercial strategies.
Bachelor's degree required; advanced degree preferred (life/physical sciences, applied sciences, computer science, mathematics, data science, or engineering).
Minimum 10+ years of pharmaceutical commercial or advanced analytics experience, with significant MMx project leadership in the US market.
Proven ability to build and operationalize Marketing Mix Models and agentic AI solutions for commercial use cases, including embedding AI into enterprise commercial workflows.
Proficiency with programming (Python, R), machine learning frameworks, pharma data sources, cloud analytics platforms, compliance with HIPAA/GDPR/CCPA, and AI governance in regulated environments.
Experienced leader adept at combining econometric and agentic AI models to drive measurable commercial outcomes and budget optimization in pharmaceutical US markets.
Strong expertise in advanced causal inference techniques, AI/ML deployment, and embedding analytics outputs into strategic brand and omnichannel decision-making.
Proven capability in mentoring analytics teams and establishing scalable, reproducible modeling frameworks within cross-functional pharma commercialization settings.