Senior Analyst, Perception Analytics & Insights

At Bristol Myers Squibb, our employees often ask, “Who are you working for?”—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it. Position Summary: The Senior Analyst, Perception Analytics and Insights, enables high-impact insight generation for the Perception Analytics group by driving advanced analytics across internal and external (social/digital) data sources. The role partners with cross-functional stakeholders to translate business questions into scalable analytical approaches. The senior analyst focuses on structuring and analyzing diverse datasets, applying business context to support tailored analyses. The role also leverages AI/ML techniques to extract meaningful signals from unstructured data and applies AI-enabled approaches such as thematic synthesis and pattern detection to accelerate insights. Additionally, the analyst contributes to reporting and innovation initiatives, with a focus on enhancing analytical depth, scalability, and decision impact through AI-driven methodologies Roles & Responsibilities Partner with business stakeholders and analytics teams to shape and deliver advanced analytics and AI-led approaches that enable data-driven decision-making. Work with large-scale structured and unstructured datasets (e.g., clinical data, publications, real-world evidence, and digital signals) to uncover insights aligned to key business questions. Apply predictive modeling and advanced analytical techniques to identify patterns, generate foresight, and support strategic and operational decisions. Leverage large language models (LLMs) and AI capabilities to enhance insight generation, including thematic analysis, knowledge synthesis, and narrative development for stakeholder-ready outputs. Enable analytics-driven AI use cases, such as knowledge-grounded querying, retrieval-based insight discovery (RAG), and intelligent assistants that improve access to insights. Shape and maintain semantic layers, taxonomies, and contextual frameworks to ensure consistent interpretation of data across analytics use cases. Define and apply evaluation approaches to assess quality, accuracy, and reliability of analytics outputs and AI-generated insights, including mitigation of bias and hallucination. Collaborate with data engineering and platform teams to ensure availability of high-quality, analytics-ready data and scalable workflows supporting repeatable insight generation.