Four (4) to six (6) years of experience. Master’s degree or equivalent experience in Data Science, Computer Science, Mathematics, Statistics, or a related field. PhD preferred. Proficiency in programming languages such as 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 working with clients and strong ability to bridge the gap between technical and business stakeholders. Ability to translate complex data science concepts into strategic business insights for non-technical stakeholders. Experience deploying models in cloud environments (AWS, Azure, or GCP) is a plus. Strong problem-solving skills, intellectual curiosity, and a proactive approach to driving impact through data science. Advanced written and spoken English fluency along with strong verbal and written communication skills.