Data Scientist, Decision Support

At ServiceNow, we make the world work better for everyone. Our global Customer Service & Support (CSS) team is at the heart of that mission—ensuring our customers have seamless, efficient, and exceptional experiences.We are looking for a Decision Scientist, Enterprise Data Management & Continuous Improvement to operationalize predictive models, design rigorous experiments, and translate insights into clear, actionable recommendations for executives. This role will help us treat data as a critical business asset—reliable, secure, compliant, and readily available to drive decision-making, innovation, and growth.About the RoleAs a Decision Scientist, you will develop, test, and scale predictive models that improve support outcomes (e.g., case volume, time-to-resolution, deflection, and containment) while maximizing capacity. You’ll design experiments, create forecasts, and deliver insights that directly shape strategy, investments, and roadmaps across CSS.Key ResponsibilitiesDevelop and maintain forecasts (volume, TTRF) and uplift/propensity models for deflection and containment.Design and analyze A/B and holdout tests across portal, IRP, and NAVA; quantify incremental impact.Build driver analyses and scenario models that tie directly to program decisions and investments.Ship production-ready features and pipelines in SQL/Python (with lightweight dbt where needed).Document and monitor model risk and Responsible AI considerations.Partner cross-functionally to drive business outcomesTranslate data-driven findings into compelling executive recommendations that influence strategy and resourcing.Continuously evaluate and improve model performance, ensuring accuracy, fairness, and business relevance.Establish and maintain data pipelines, monitoring, and reporting frameworks to ensure insights are timely, reliable, and actionable.Champion a data-driven culture within CSS by coaching peers, enabling self-service analytics, and sharing best practices.Track and communicate emerging trends in predictive analytics, AI/ML, and experimentation; recommend adoption where impactful.Support compliance, privacy, and governance requirements in all modeling and experimentation practices.