Top Senior Analytics Jobs in Oklahoma City, OK

Lead a team of analysts and data scientists embedded in sales to build rigorous pilot analyses, create executive-ready business cases, expand consultative analytics across the partner lifecycle, and publish industry insights while coaching and scaling the Solutions Analytics function.

Senior analytics leader who defines analytic strategy, leads a team of SQL analysts and BI developers, architects scalable frameworks for medical economics, risk, population health and value-based care, ensures methodological rigor in DBT/Spark and Quicksight dashboards, drives automation and AI integration, presents to executive stakeholders, and mentors senior analytic talent.

Lead growth analytics for Zendesk’s product-led growth motion, guiding a team of analysts and partnering with Product, Engineering, Sales, Marketing, and Data teams. Define funnel metrics, measurement plans, experiments, and instrumentation across acquisition, activation, conversion, retention, and expansion. Analyze customer behavior using segmentation, cohorts, funnels, experimentation, and statistical methods. Improve self-service reporting, dashboards, metric definitions, reusable datasets, and analytics capabilities while coaching analysts and influencing senior stakeholders.

Lead pricing analytics for merchant/platform deals and international market expansion. Define pricing strategy, run economic analyses, design and test pricing constructs, and collaborate with product, partnerships, credit, finance, capital markets, and engineering to optimize portfolio performance.

Own the Finance and Operations data layer, integrating systems into Snowflake and Omni, building reusable data models, dashboards, governed metrics, validation checks, and reconciliation workflows. Partner with Finance, Operations, and Data teams to translate business processes into trusted analytics, improve data quality, automate reporting, and support leadership decision-making.

Own and evolve the analytics platform, including data models, pipelines, metric definitions, semantic layers, dashboards, and self-service data products. Partner with cross-functional stakeholders to translate business needs into reliable technical solutions. Lead data initiatives, improve ELT reliability and governance, resolve quality issues, mentor teammates, and shape the Analytics team’s technical roadmap. The role requires strong SQL, dbt, modern data-stack experience, business communication, and independent execution in an ambiguous environment.

Designs and maintains enterprise data pipelines, warehouses, lakes, semantic models, ETL/ELT processes, and SQL solutions. Supports Power BI datasets and reporting architectures while ensuring data quality, governance, security, and performance. Collaborates with HR stakeholders, analysts, data scientists, and technology teams to translate business requirements into scalable technical solutions. The role also contributes to data architecture, troubleshooting, documentation, and engineering best practices.

Owns retention analytics for a new Loyalty & Retention organization, including churn definitions, survival analysis, forecasting, experimentation, acquisition attribution, satisfaction analysis, payment recovery, and save-desk performance. The role builds reporting and predictive models from scratch, partners with BI and actuarial teams, influences cross-functional decisions, and presents retention findings and forecasts to executives.

Leads enterprise analytical modeling and semantic architecture, establishes standards for testing, documentation, governance, lineage, observability, and access, and develops reusable governed data products. Partners across Product, Engineering, Finance, Clinical, Research, Marketing, and AI teams; guides architecture reviews, data quality ownership, semantic layer design, and governance adoption. Mentors engineers and drives modernization of analytical environments.

Analyzes web, customer, and campaign data to generate actionable digital marketing insights. Builds dashboards and presentations using Adobe Analytics, Power BI, or Tableau; evaluates site performance, media monetization, A/B tests, and web projects; supports tagging, reporting validation, and vendor implementations. The role partners with stakeholders and Agile teams, manages analytics priorities, and communicates findings to guide marketing strategy and business decisions.

Analyzes paid media performance across the full funnel, connecting spend and platform metrics to applications, enrollment, student lifetime value, and ROAS. Builds attribution frameworks, Databricks data pipelines, Power BI dashboards, semantic models, and advanced DAX reporting. Supports marketing mix modeling, experimentation, web analytics data quality, forecasting, governance, and workflow automation. Translates complex analytics into strategic recommendations for executive and cross-functional stakeholders.

Designs, develops, and sustains cloud-based data analytics infrastructure and ETL pipelines. Manages data retention, curation, cataloging, schemas, and automation across AWS, Elasticsearch, and Google Analytics platforms. Creates visualizations and reports using Kibana, AWS QuickSight, and Google Analytics 4. Supports cloud-native architecture, infrastructure automation, DevOps, monitoring, troubleshooting, bug fixes, and customer support.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Own SQL and dbt-based data modeling and data quality for clinical and claims datasets. Author and refactor dbt models/tests, triage DQ alerts, design monitors, optimize SQL performance, and collaborate with Data Engineering and stakeholders to ensure trusted production datasets.

Lead end-to-end analytical initiatives on partner enrollment funnels, ensure data quality, build reporting pipelines with BI/engineering, use AI-assisted tools to accelerate analysis, translate insights into strategic recommendations for leadership, and coach growing analytics team members.

Lead product analytics for Guest or Host App: analyze large datasets, design and evaluate experiments, build metrics and reporting tools, apply statistical and causal methods, partner cross-functionally, present insights to stakeholders, and leverage AI to automate tasks.

Transforms enterprise IT operations, monitoring, KPI, and performance data into executive dashboards, heatmaps, trend analyses, forecasts, anomaly detection, and narrative insights. Integrates data from monitoring, ticketing, incident, and operational systems; develops standardized reporting templates; documents analytical workflows; and collaborates with engineering, service desk, cybersecurity, and PMO teams to support federal reporting and leadership decisions.

Designs and maintains executive dashboards, reports, semantic models, and automated analytics solutions using Power BI. Defines enterprise KPIs, data standards, and business rules while integrating data from ERP, CRM, manufacturing, SQL, and cloud systems. Partners cross-functionally with senior leaders to deliver insights, improve data quality, support master data management, and enable scalable self-service analytics and data-driven decision-making.

Leads analytics engineering and analytics-ready data architecture for government clients. Designs standardized data models, transformation logic, validation frameworks, and reusable integration patterns. Governs data quality, QA, backfills, and release processes while resolving complex data issues. Integrates web, email, social, survey, and client-system data to support dashboards, reporting, measurement, and insights. Advises stakeholders, influences enterprise standards, coordinates with product teams, and supports client-facing analytics workstreams.

Leads enterprise business intelligence and analytics strategy, owning the vision, roadmap, KPIs, and adoption measures for insight products. Manages data engineering and analytics teams, partners with senior leaders, translates business questions into analytical solutions, and delivers executive-ready insights. Provides technical oversight for data models, pipelines, semantic layers, data quality, scalability, and metric standardization across transformation, sales, operations, sustainability, and other enterprise domains.

Designs, develops, tests, and deploys reports, dashboards, and analytics solutions using UKG Pro HCM or Pro WFM. Provides report design, application build support, training, testing, go-live support, change management, documentation, and client consultation during implementations and migrations. The consultant also contributes to internal methodologies, mentors colleagues, and supports sales and marketing initiatives. The role requires SQL, BI tools, advanced Excel, UKG reporting expertise, and up to 10% nationwide travel.

Build and operate reliable ETL and ELT pipelines across lakehouse and transactional systems. Develop data models, enforce governance, integrate diverse data sources, and support analytics, APIs, and predictive tools. Monitor performance, data quality, lineage, cost, and uptime while collaborating with data science, AI, product, and innovation teams.

Lead enterprise adoption and toolchain integration for business analysis across federated teams. Design enablement curriculum, integrate standards and AI-enabled tooling (Azure DevOps, ServiceNow, Nexus, Power BI), build decision-oriented dashboards and leading indicators, drive adoption and governance, surface portfolio trends, and partner with stakeholders to improve delivery predictability and compliance.

Leads web analytics strategy, GA4 and GTM implementations, tagging specifications, dashboards, reporting, experimentation, and data-quality monitoring. Analyzes user behavior, conversion funnels, feature adoption, and A/B test results to provide actionable recommendations for product and business decisions. Partners with product, engineering, UX, and business stakeholders and communicates analytical findings to technical and non-technical audiences.

Own marketing channel performance analysis, reporting, experimentation, dashboards, and measurement frameworks. Develop incrementality, LTV, and forecasting analyses; identify data quality risks; and translate complex findings into actionable recommendations for Marketing, Growth, and Finance stakeholders. The role requires strong SQL, BI reporting, marketing measurement, experimentation, and analytical communication skills, with AI tools used to accelerate analytics workflows.