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Tier-1 employer, mid-level experience, metro location, and broad analytics skillset increase candidate competition.
Advanced analytics and omnichannel measurement skills are transferable, though pharma experience is preferred.
Explicit 3–5 years requirement plus mandatory analytics, Python/R, and attribution experience makes filtering strict.
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Deliver end-to-end measurement analyses of omnichannel customer engagement using machine learning and advanced statistical techniques.
Support design and execution of AI-informed experiments (A/B tests, lift studies) and operationalize measurement frameworks and KPIs.
Partner with commercial stakeholders to communicate insights, develop dashboards and frameworks, and mentor junior analysts on advanced methods.
Bachelor’s degree required; advanced degree preferred in data science, analytics, statistics, mathematics, economics, life sciences, computer science, or engineering.
3–5 years of professional experience in advanced analytics, decision science, or omnichannel engagement measurement, ideally in AI-driven commercial environments.
Experience with attribution and impact measurement techniques (multi-touch attribution, causal inference, uplift modeling) is a strong plus.
Proficiency in Python or R required; experience with cloud analytics platforms (Databricks, Snowflake) preferred.
Experienced in advanced statistical and AI/ML analytics with deep focus on omnichannel customer engagement measurement in pharma or healthcare.
Comfortable operating cross-functionally with commercial, digital, CRM, and tech teams in a matrixed environment communicating complex analytics to diverse stakeholders.
Skilled at building repeatable analytics frameworks, automating workflows, and mentoring teams to ensure analytical rigor and data governance compliance.