Qualification Requirements Master's degree or equivalent experience in Data Science, Computer Science, Mathematics, Statistics, or a related field. PhD is preferred. Proficiency with programming languages like Python, R, and SQL. Experience applying causal inference techniques (e.g., causal impact analysis, uplift modeling, DoWhy) to marketing and engagement analytics. Strong background in predictive modeling, classification, segmentation, and optimization. Familiarity with healthcare and commercial biopharma data sources such as claims data, HCP interaction logs, and prescription data. Experience engaging with clients and strong ability to bridge the gap between technical and business audiences. Ability to translate complex data science concepts into strategic business insights for non-technical stakeholders. Experience deploying models in cloud-based environments (AWS, Azure, or GCP) is a plus. Strong problem-solving skills, intellectual curiosity, and a proactive approach to driving impact through data science. Skill (Primary): Quality Management Skills (ERS)-Techniques-Data Science