Top Analysis Reporting Jobs in St. Louis, MO

Leads analytics, reporting, data modeling, automation, AI-agent development, and quality assurance for revenue cycle operations. Creates Power BI and Excel reports, analyzes complex healthcare and operational datasets, develops scalable warehouse models, and delivers actionable insights to leadership. Uses SQL, cloud data platforms, Git, Python, and AI-assisted tools to improve reporting efficiency, accuracy, and decision support.

Builds and maintains Power BI reports, dashboards, data models, DAX calculations, and row-level security. Writes SQL queries for reporting, analysis, and data validation; investigates warehouse structures and inconsistencies; and partners with stakeholders and data teams to deliver accurate insights. The role manages recurring and ad hoc reporting requests, communicates findings through data visualization, and supports business decisions across sales, marketing, and operations.

Supports medical education evaluation and grant-seeking through data manipulation, statistical analysis, reporting, visualization, and stakeholder communication. The role prepares reports, presentations, conference abstracts, and publications using Excel, R, SPSS, SAS, and related tools. It also explores open-ended evaluation questions, manages multiple projects, and applies generative AI to accelerate report drafting, data validation, formatting, and deliverable quality assurance.

Collects and researches equipment cost data for quarterly product updates, performs data analysis, and supports ownership and operating cost calculations. Maintains reports and dashboards, responds to data requests, audits processes, improves documentation, and partners with engineering and data quality teams to streamline workflows and ensure reliable, high-quality data.

Manages enterprise data governance and privacy compliance programs, including GDPR and CCPA adherence, data subject rights processes, governance controls, privacy documentation, compliance metrics, and continuous improvement. Coordinates with business, legal, compliance, security, and technology stakeholders; maintains process documentation; monitors risks and response timelines; supports automation, reporting, awareness training, and audit readiness across global operating units.

Lead marketing analytics: own reporting frameworks, dashboards, and data quality; monitor KPIs; run A/B tests and experiments; build attribution, forecasting, segmentation, and budget-allocation models; automate workflows and drive continuous measurement improvements.

Work with clients and technology teams to gather and translate business requirements into technical user stories and solutions, propose process improvements, and communicate effectively with stakeholders. Assist in analytical solution delivery and may write/execute SQL queries.

Lead a small business intelligence team while remaining hands-on with SQL, Power BI, reporting, forecasting, commercial analysis, and executive insights. Own the analytics roadmap, KPI frameworks, dashboards, data governance, and business logic. Partner with sales, marketing, executives, and data engineers to improve reporting and data quality. Mentor analysts and translate business questions into actionable recommendations for a B2B SaaS organization.

Own advanced analytics for Airbnb product teams, using large datasets, statistical modeling, experimentation, causal methods, forecasting, and metrics development to guide product and business decisions. Build reporting and analytical tools, collaborate cross-functionally, automate repetitive work with AI, and present actionable insights to senior stakeholders. The role supports Guest App or API initiatives, including promotions and marketplace optimization.

Conduct product analytics for MoneyGram’s digital money transfer products. Analyze customer behavior, product performance, experiments, feature releases, and cohort metrics to guide product strategy and growth. Build insights and reporting, collaborate with Product, Engineering, Marketing, Finance, and international teams, and improve analytics platforms, automation, and visualization processes. Translate complex findings into actionable recommendations for technical and non-technical stakeholders.