Top Analysis Reporting Jobs in Kansas City, MO

Lead product analytics for usage, activation, adoption, retention, and expansion. Define metrics, improve instrumentation, build reusable measurement frameworks, apply AI-first analytics workflows, design experiments and observational analyses, create monitoring/alerting, surface insights to influence product decisions, and mentor analysts.

Design, develop, and optimize scalable database solutions (ODS/warehouse) to support enterprise analytics and operational reporting. Lead architecture, project management, and standards; collaborate with analytics teams and leadership on interfaces and specifications; monitor performance and SLAs; implement ETL, data modeling, SQL tuning, and data integration; maintain development standards and evaluate technical approaches.

Analyze user behavior, feature adoption, and retention across a B2B SaaS platform to generate evidence-based product insights. Track journeys, run cohort and funnel analyses, support A/B testing, define product KPIs, ensure data accuracy, and provide structured recommendations to inform roadmap and improve adoption and retention.

Lead end-to-end quantitative research projects for assigned clients: scope, design surveys, define samples, analyze data, and deliver client-ready insights and recommendations. Serve as primary client contact, guide clients to full-service or DIY solutions on Numerator's platform, use AI-enabled tools responsibly, mentor analysts, support sales and consulting efforts, and manage multiple projects while protecting scope, quality, and timelines. Travel as required.

Lead day-to-day management of multi-year data projects (Neighborhood Vitality Index, Hope Starts Here). Conduct quantitative and qualitative analysis, design and analyze surveys, coordinate with external partners and internal teams, perform stakeholder outreach and engagement, and produce accessible data products and communications for non-technical audiences to inform decision-making across Detroit-area organizations.

The role involves analyzing complex pricing strategies, conducting data-driven analyses, collaborating with cross-functional teams, and translating insights into strategic business recommendations.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

The role involves building and scaling a Closed-Loop Design Program that enhances pre-sales engineering through data science and analytics in supply chain automation.

Develop and optimize SQL-based data solutions and ETL/ELT pipelines using DBeaver. Troubleshoot data quality and performance, validate data prior to production, document transformations, and collaborate with application owners and business stakeholders. Support testing, deployments, and knowledge transfer in a healthcare data environment.

Design, build, and maintain scalable data systems and ETLs on GCP; connect production data to business systems; generate analytics and ML-driven insights for GTM teams; work cross-functionally and introduce modern tools (Airflow, DBT, Presto, Hightouch).