job description
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.
Skill (Primary) Quality Management Skills (ERS)-Techniques-Data Science
Kind & Regards
