Senior Analyst, Perception Analytics & Insights

Requirements

• BA/BS required; advanced degree preferred with special consideration for degrees in life/physical sciences, applied sciences (computer science, mathematics, data science), or engineering
• 3-5 years career experience preferred, including 2+ years of experience in data analytics.
• Ability to translate business questions into actionable analytics and reporting
• Strong written and verbal communication skills, with the ability to simplify complex information
• Proven ability to work collaboratively in a fast-paced, matrixed environment
• Technical Skills (Preferred)
• Strong foundation in analytics, machine learning, and predictive

Additional Information

Working with Us Challenging. Meaningful. Life-changing. Those aren't words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You'll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible. Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us . 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. Translate complex analyses into clear, actionable insights through concise storytelling, visualizations, and executive-ready presentations for both technical and non-technical audiences. Skills and competencies Strong foundation in machine learning and predictive analytics, with ability to solve complex business problems using data-driven approaches. Proficiency in Python and SQL, with experience working on large datasets and building scalable analytical workflows on modern platforms (e.g., Databricks, Spark). Hands-on experience leveraging LLMs and AI techniques for analytics, including retrieval-augmented insights, text analytics, and knowledge synthesis from unstructured data. Understanding of embedding-based approaches, vector search, and semantic data modeling, enabling contextual analytics and improved insight discovery. Familiarity with agentic AI frameworks, multi-step workflows, and LLMOps practices (prompt design, evaluation, monitoring) to support scalable AI-driven analytics. Strong communication and storytelling skills, with the ability to translate complex analytical and AI concepts into actionable insights for diverse stakeholders.

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