Top Analytics Jobs in Kansas City, MO

Partner with business teams to scope and execute analyses, generate actionable insights from large healthcare datasets, build dashboards and models, present findings to leadership, own stakeholder relationships for a major business unit, and monitor impact of improvement initiatives.

Partner with business teams to scope, run, and present analytical projects that monitor financial and utilization metrics. Own insights generation for a major business unit, build dashboards and models to surface healthcare inefficiencies, maintain stakeholder relationships, and support strategic projects to drive improvements and measure impact.

The Predictive Analytics Consultant designs and delivers analytics solutions for lending operations, focusing on predictive modeling, data transformation, and stakeholder communication.

Consult with financial institutions to analyze consumer credit and loan performance, evaluate underwriting and decision rules, develop data-backed lending recommendations, produce client reports/dashboards, and lead engagements using MeridianLink decisioning platforms and BI tools.

Build and operate the core BI platform: own ingestion, integration, modular dbt pipelines, and enterprise data models. Establish data quality, testing, governance, observability, and CI/CD. Monitor platform health, certify pipelines and data products, and mentor analytics engineers to enable trusted, self-service analytics and AI-augmented workflows.

Lead analytics and BI for Digital Product Operations: define product and adoption metrics, build dashboards, ensure data governance and quality, measure ProdOps effectiveness, coach PM/POs, diagnose adoption gaps, and drive interventions that improve product planning and delivery.

Lead demand forecasting and performance analytics for eCommerce: build forecasting models, run scenario and promotional analyses, produce executive reporting, drive cross-functional predictive initiatives, and deliver market and competitive insights to inform planning and resource allocation.

Lead analytics for the Credit Card portfolio, partnering with Product, Engineering, Credit Risk, Fraud, and Marketing to deliver data-driven strategy. Perform ad-hoc and cohort analyses, design A/B tests, manage BI reports, drive portfolio growth and risk insights, and build scalable data solutions with Data Engineering. Influence executives through clear recommendations and leverage AI tools to accelerate analytics and self-service.

Serve as embedded BI lead for a divisional sales book, delivering actionable insights from syndicated and commercial data, leading opportunity analysis, training field teams, supporting Power BI reporting, and translating complex data into executive presentations to drive sales performance and planning.

Lead end-to-end category insights for strategic account chains using syndicated, retailer POS, and internal data. Develop analyses, reporting, and recommendations to drive sales and profit, partner with sales and BI, support category reviews and business planning, and present insights to stakeholders.

Serve as embedded BI partner for an assigned division, delivering actionable commercial insights from syndicated and internal data, leading opportunity analyses, training field teams, supporting Power BI reporting, and translating complex data into executive presentations to drive sales performance and program ROI.

Lead process mapping, analysis, and redesign to improve efficiency and outcomes. Partner with stakeholders to gather requirements, analyze data (SQL, Excel, Power BI), define KPIs, apply Lean/Six Sigma methods, and support automation and digital transformation initiatives to drive growth, profitability, and loss reduction.

Implement, QA, and document tag management and data-layer specs across GTM, GA4, server-side pipelines, Shopify, and native apps. Collaborate with product and engineering to ensure tracking, pixel integrity, attribution, and experimentation event fidelity; support monthly audits, consent enforcement, and maintain centralized solution design documentation.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

The Director of Product Analytics leads the product analytics strategy, develops a team of analysts, drives insights for product decisions, and oversees experimentation across products to enhance growth outcomes.

Lead product analytics efforts to define KPIs, build measurement frameworks, analyze customer behavior, and generate insights that influence product and engineering decisions. Partner with Product, Engineering, and Data teams to design event tracking, run experiments, quantify opportunity sizes, and communicate recommendations through clear narratives and visualizations to drive product adoption, retention, and business outcomes.

Lead BI developer who owns reporting infrastructure end-to-end: SQL-based data extraction from messy sources, LookML/BI model development, dashboard standardization, stakeholder partnership, and performance marketing optimization to drive actionable insights and business outcomes.

Lead a team to analyze sales data, build and maintain Power BI and Excel reporting, leverage AI and automation for pipeline and lead scoring, align cross-functional GTM strategies, ensure data quality, and deliver actionable, executive-ready insights to drive sales performance and quota attainment.

Design, build, and operationalize scalable analytics engineering solutions on Databricks and modern cloud platforms. Implement metrics-as-code and semantic layers, create automated pipelines, enable product measurement and experimentation, define cohorts and KPIs, improve data quality and governance, and lead engineering best practices and stakeholder delivery for data products.

Deliver executive-ready commercial banking insights by building driver-based forecasts, monitoring portfolio performance, identifying strategy gaps, partnering cross-functionally, communicating findings to senior leaders, and mentoring junior analysts to drive data-driven decisions and measurable business impact.

Perform analysis of loan servicing strategies, monitor champion/challenger tests, develop complex data extraction and manipulation code, produce performance reports, and translate business goals into technical tasks to optimize high-volume decisions.

Lead and grow an enterprise analytics practice for B2B commerce and marketing: define measurement strategy, implement tracking and data ecosystems, build KPI frameworks and dashboards, ensure data governance and quality, mentor analysts, deliver insights that drive client decisions and business outcomes, and support client growth and proposals.

Design and maintain enablement resources that help data and analytics practitioners discover assets, adopt tools, and develop skills. Build ownership directories, onboarding content, sample code, and training materials. Partner with platform teams, governance, and stakeholders to validate guidance, drive adoption, run technical events (datathons, workshops), and improve the practitioner experience across the enterprise.

Produce and validate default reporting and analytics for mortgage servicing portfolios. Investigate data discrepancies, perform root-cause analysis, modify reports for ad-hoc needs, document processes, and collaborate with default management to ensure regulatory and investor-compliant reporting.

Own end-to-end analytics modeling for a business domain: build and maintain dbt models and business marts on Snowflake, develop the BI semantic layer, define consistent metrics, create self-serve data products, and partner with Finance, Sales, Marketing, CS, and RevOps. Validate upstream data with the Data Platform team and translate ambiguous business questions into production-ready data models.