- Designing and implementing analytical frameworks.
- Healthcare and commercial biopharma data sources such as claims data, HCP interaction logs, and prescription data.
- Developing predictive and prescriptive models.
- Lead the design and execution of advanced machine learning and causal inference models to measure and optimize omnichannel engagement strategies.
- Experience applying causal inference techniques (e.g., causal impact analysis, uplift modeling, DoWhy) to marketing and engagement analytics.
- Exercise independent judgment in methods, techniques, and evaluation criteria on data science projects, overseeing the end-to-end process from problem definition to model implementation.
- Proficiency with programming languages like Python, R, and SQL.
- Strong background in predictive modeling, classification, segmentation, and optimization.
Extensively worked in Azure Cloud environment.