Top Senior Analytics Jobs in St. Louis, MO

Lead design and delivery of Workday reporting and analytics for AMS clients: build advanced/matrix/trending/composite reports, dashboards, Discovery Boards, Worksheets, and complex calculated fields; gather requirements, optimize reports, mentor junior consultants, and provide Workday best-practice guidance.

Lead architecture and execution of Grafana's marketing data stack and analytics practice. Build forecasting, predictive, and causal models, design BigQuery schemas, deploy agentic AI and automated pipelines, partner with GTM leadership, and deliver executive-grade insights to drive demand generation and ROI.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

The Senior Data Scientist will build frameworks for data-driven decision making, develop predictive models, ensure data quality, and enhance customer experiences through analytics and operational insights.

Lead Oracle Cloud reporting initiatives, ensuring data accuracy and performance while mentoring junior analysts and collaborating with stakeholders.

The Analytics Lead will guide data-driven decision-making, develop measurement frameworks, forecast revenue, and mentor an analytics team, ensuring effective communication of insights.

Lead a centralized Decisioning Analytics team to measure and optimize Pega-powered Next-Best-Action decisioning. Own measurement frameworks, ADM performance, transparency, governance, cross-functional partnerships, NBA analysis, roadmap, and team development to drive measurable customer and financial outcomes.

As an Analytics Engineer, transform raw data into metrics, manage data pipelines, ensure data integrity, and collaborate with teams for analytics solutions.

The Senior Data Analytics Engineer will develop data pipelines, support data-driven decision-making, collaborate with stakeholders, and improve data quality and processes.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

Lead analytics for Omnichannel retail/restaurant/CPG partners: act as primary analytics contact for Sales, manage analytic engagements and team capacity, perform SQL-based analysis, craft data-driven narratives and recommendations, influence campaign strategy, represent analytics in cross-functional settings, and automate insights using AI-enabled tools.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Build and own the quality analytics data layer: design and maintain dbt models, data marts, and Python-driven analyses. Define and standardize quality metrics, run experiments and A/B tests, support decision-making with dashboards and reports, automate recurring reporting, and partner with Quality and Engineering to ensure reliable, documented analytics.