Description

You will design and implement analytical frameworks for commercial pharma data science problems.

Responsibilities

• Develop predictive and prescriptive models using healthcare and commercial biopharma data sources like claims, HCP interaction logs, and prescription data.
• Lead the design and execution of advanced machine learning and causal inference models to optimize omnichannel engagement strategies.
• Apply causal inference techniques, such as causal impact analysis, uplift modeling, and DoWhy, to marketing and engagement analytics.
• Exercise independent judgment on data science projects, owning the process from problem definition through model implementation.

Required Skills

• 12+ years of professional experience in a data science role.
• Proficiency in Python, R, and SQL.
• Strong background in predictive modeling, classification, segmentation, and optimization.
• Extensive experience working in the Azure Cloud environment.
• Experience applying causal inference techniques to marketing and engagement analytics.

Key Skills

Education

Not specified