Sr. Analyst, US Customer Engagement Measurement & 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. Senior Analyst, Customer Engagement Measurement & Insights Role Summary The Senior Analyst, Customer Engagement Measurement & Insights is an AI-enabled analytics practitioner responsible for supporting the measurement, analysis, and optimization of omnichannel customer engagement across HCP and patient touchpoints. As a part of Customer Engagement Measurement & Insights team, this role delivers campaign performance insights, experimentation outputs, and data-driven recommendations that inform channel strategy, engagement effectiveness, and commercial decision-making. The Senior Analyst executes analyses that feed into attribution models, test-and-learn initiatives, and omnichannel performance reporting. This role requires strong engagement measurement, causal inference, and advanced analytics skills and the ability to translate data-driven signals into clear, actionable business recommendations that support an AI-powered commercial strategy Roles & Responsibilities Customer Engagement Measurement & Analytics Delivery Independently delivered measurement analyses assessing the effectiveness of omnichannel customer engagement across field, CRM, paid media, owned digital, and third-party channels. Apply machine learning techniques to identify patterns in customer engagement, channel synergy, sequencing, pacing, and message performance. Support the development and operationalization of measurement frameworks, KPI tracking tools, and performance dashboards aligned with the team's strategic priorities. Synthesize analytical findings into clear, structured outputs and actionable recommendations for internal stakeholders and team leads. Experimentation & Test-and-Learn Support Support the design and execution of AI-informed test-and-learn strategies , including A/B tests, lift studies, and incrementality experiments across customer engagement tactics. Assist in defining success metrics, measurement windows, and statistical approaches to evaluate new engagement strategies. Contribute to the documentation and socialization of experimental learnings to inform ongoing campaign planning across brands. Help refine experimentation frameworks to accelerate learning cycles and improve engagement effectiveness. Advanced Analytics & Attribution Apply advanced statistical and AI/ML techniques to measure the incremental impact of customer engagement activities. Support the use of attribution frameworks such as multi-touch attribution, Markov chain modelling, and causal inference methods (e.g., propensity scoring, matched control). Contribute to the integration of outputs from MMx, KDA, and predictive models to support engagement optimization strategies. Leverage automation to improve speed, consistency, and repeatability of insights delivery. Stakeholder Partnership & Communication Partner with US Commercial stakeholders, Brand, Omnichannel Strategy, Field Analytics, CRM, Digital, and Technology teams to contribute to AI-enabled measurement solution design. Clearly communicate measurement methodologies, assumptions, model limitations, and implications for decision-making to both technical and non-technical audiences. Contribute to stakeholder presentations and working sessions with structured, insight-driven storytelling focused on impact and commercial actions. Team Collaboration & Capability Building Collaborate within cross-functional and global teams to ensure consistent, scalable, and governed analytical delivery aligned with AI best practices. Mentor junior analysts on advanced measurement methodologies, analytical rigor, and responsible data usage. Contribute to the development of reusable analytics frameworks, measurement templates, and best practices that scale across brands. Promote high standards of reproducibility and documentation across all team deliverables. Technical Execution & Data Stewardship Build and maintain AI-enabled measurement datasets, dashboards, and automated workflows supporting omnichannel engagement analytics. Work closely with data engineering, technology, and build teams to troubleshoot data issues and provide measurement-driven feedback to enhance commercial solutions. Ensure analytical outputs are reproducible, well-documented, and aligned with data governance, compliance, and responsible use standards. Skills & Competencies Strong written and verbal communication skills with the ability to translate complex analytics and engagement insights into clear business outcomes, including AI-generated findings. Solid project execution and organizational skills, with the ability to manage multiple analytical workstreams in parallel. Strong analytical thinking and problem-solving skills, with attention to detail, data quality, and measurement rigor. Hands-on expertise in applied statistics, analytics, and advanced measurement concepts relevant to omnichannel performance. Familiarity with HCP and patient engagement journeys across digital, field, and media channels. Collaborative mindset with the ability to work effectively in a matrixed, stakeholder-driven environment. Curiosity and passion for learning, innovation, and continuous improvement in analytics and measurement. Experience & Qualifications BA/BS required; advanced degree preferred in data science, analytics, statistics, mathematics, economics, life sciences, computer science, or engineering. 3–5 years of professional experience in advanced analytics, decision science, or omnichannel engagement measurement roles, ideally within an AI-driven commercial environment. Proven experience delivering end-to-end analytics and measurement projects, from problem framing to insight delivery. Experience with attribution and impact measurement techniques (e.g., multi-touch attribution, causal inference, uplift modeling) is a strong plus. Demonstrated ability to partner with business stakeholders and support data-informed decision-making. Experience in pharmaceutical, biotech, or healthcare industries preferred. Proficiency in Python or R for analytical modeling and data transformation. Experience with cloud-based analytics environments (Databricks, Snowflake, or equivalent) preferred. Technical Skills (Preferred) Predictive and statistical analytics using Python and SQL, including uplift modeling, drivers analysis, propensity modeling, and causal inference methods. Familiarity with attribution frameworks such as multi-touch attribution and Markov chain modeling. Experience working with performance metrics, model diagnostics, and AI-enabled analytics outputs. Data visualization and dashboarding tools (e.g., PowerBI, Tableau, Dash, or similar platforms). Experience in collaborative analytics environments (e.g., Databricks, Git-based workflows, SharePoint). Familiarity with omnichannel, CRM, digital marketing, and commercial data sources. Practical exposure to LLMs and generative AI as an insight and enablement layer, including prompt design for classification, summarization, and insight generation. We hire for skills and capabilities, not just credentials – if this role excites you, but doesn’t perfectly match your resume, we encourage you to apply anyway. How We Work Where you work matters – because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models: site-essential, site-by-design, field-based and remote-by-design. The model assigned to this role is based on its core responsibilities. Learn more at . 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