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Strong pharma brand, metro location, mid-level role but niche pharma AI skills limit candidate pool.
Requires deep pharma commercial analytics and datasets, limiting transferability across industries.
Multiple mandatory requirements: 7+ years, pharma analytics experience, hands-on agentic AI and domain-specific datasets.
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Co-own and drive the strategy, roadmap, and evolution of the Agentic MMx and Always on Insights self-service analytics platforms, integrating advanced analytics and AI-driven decision support into commercial workflows.
Lead technical oversight, governance, and compliance for analytics products ensuring data/model health, auditability, privacy, and regulatory compliance in pharma commercial settings.
Partner across global commercial stakeholders and analytics teams to align AI product development with business priorities, enabling ROI-driven investment and sustained adoption through training and enablement.
Advanced degree (MS/PhD preferred) or strong relevant experience in Data Science, Statistics, Computer Science, Econometrics, or related quantitative field.
Minimum 7 years of hands-on experience in pharmaceutical commercial analytics or decision science developing and deploying production-grade AI analytical solutions.
Experience managing analytics talent and leading cross-functional teams in a global enterprise environment.
Work Experience Required: At least 7 years in pharma commercial analytics or decision science; onsite presence expected as per company policy (site-essential or site-by-design roles).
Experienced in building and operationalizing agentic AI solutions including multi-agent systems, LLMs, real-time analytics, and integration into enterprise commercial workflows.
Strong collaborator able to manage competing demands across time zones and align stakeholder needs with technical product roadmaps and governance.
Technically proficient with programming (Python/R), machine learning frameworks, causal inference methods, BI and cloud platforms; capable of driving innovation and AI governance in regulated environments.