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Tier-1 brand and metro location increase competition, while seniority and niche HCP omnichannel analytics reduce applicant density.
Requires deep HCP/patient omnichannel expertise, making background fit highly industry-specific and less transferable.
Mandatory 10+ years, domain-specific HCP analytics, causal inference expertise, and Python/cloud requirements make shortlisting highly strict.
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Develop and implement measurement frameworks to assess effectiveness of omnichannel customer engagement across multiple channels including field, CRM, paid media, and digital.
Design and execute test-and-learn strategies (e.g., A/B testing, lift studies) to optimize engagement tactics and collaborate with marketing and CRM teams to apply insights.
Lead advanced analytics and attribution efforts using techniques like Markov chain modeling and machine learning to guide engagement optimization and build reusable measurement frameworks.
Bachelor’s degree in Data Science, Analytics, Statistics, Economics, or related field.
10+ years of experience in advanced analytics or data science focused on omnichannel engagement measurement.
Proficiency in Python or R for analytics and data transformation; experience with cloud-based analytics environments (e.g., Databricks, Snowflake).
Strong expertise in attribution and impact measurement methods including multi-touch attribution, Markov chains, and causal inference methods.
Experienced in measuring and optimizing customer journeys specifically for Healthcare Professionals (HCP) and patients across digital, field, and media channels.
Skilled in applying and mentoring on advanced analytics including causal inference, attribution modeling, and experimentation frameworks.
Able to translate complex analytical insights into actionable business strategies driving measurable commercial outcomes in cross-functional environments.