Top Senior Analytics Jobs in Tulsa, OK

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Design and maintain a formal analytics data layer (AWS Glue, Athena/Presto, LookML); build data models, pipelines, and automated quality checks; investigate anomalies; document metrics and lineage; mentor analytics team members and promote best practices.

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

Lead analytics strategy and delivery for healthcare clients: gather reporting requirements, design and build enterprise data platforms (Databricks/lakehouse), develop and validate reports (including Epic reporting), influence decentralized data teams, and provide post-implementation support and modernization.

Lead analytics and data-product initiatives for healthcare clients: gather reporting requirements, design and develop reports/products, test and validate, provide post-implementation support, and partner with stakeholders to drive adoption and measurable value.

Lead-level analyst who designs, develops, and delivers reports, dashboards, and data solutions (SQL, Power BI, SSRS, Excel). Analyzes complex healthcare, financial, and operational data, ensures data quality and ETL processes, mentors analysts, manages analytics projects, drives automation and process improvements, and presents insights to leadership and stakeholders.

Lead identification and quantification of issuance leakage across acquisition, application, approval, and funding funnels. Analyze digital customer journeys and conversion gaps, run root-cause diagnostics, design experiments, build executive dashboards, and translate findings into prioritized, quantified business recommendations partnering with Product, Marketing, Credit Risk, Operations, and Engineering.

Lead design and governance of enterprise ontologies, knowledge graph architecture, ingestion pipelines, and semantic layers. Enable semantic interoperability across data products, implement inference and reasoning, and establish standards, versioning, and data contracts to support scalable graph-driven analytics and AI augmentation.

Lead design and implementation of data models, write optimized SQL at scale, enable semantic layers and AI tooling, manage analytics infrastructure, build frontend data surfaces, and partner with product and engineering to structure source systems for reporting.

Lead a team to develop data strategy and insights across multiple business functions, driving analytics evolution and ensuring data quality and governance.

Own marketing channel performance tracking, reporting, and analysis. Design and analyze experiments (A/B, incrementality), build dashboards in Looker/Tableau, support LTV and forecasting models, identify measurement gaps, and translate analysis into clear recommendations for Growth, Marketing, and Finance stakeholders.

As a Director in the Data & Analytics team, you will lead client engagements, manage projects, develop strategies, create proposals, and mentor team members in data-driven initiatives.

The Senior Data Engineer will design, build, and support data environments, orchestrate pipelines, and implement data solutions for advanced analytics and machine learning, working closely with project teams.

As a Revenue Analytics Manager, you will own reporting for Sales, Marketing, and Customer Success, build dashboards, automate workflows, and ensure data quality.

Own metrics and datasets that measure cloud, storage, streaming, and ML infrastructure efficiency. Build end-to-end analytics: metric frameworks, pipelines, dashboards, and narratives that inform executive and engineering investment decisions. Pioneer methods to quantify AI and agent-driven productivity, identify efficiency opportunities, and partner with data engineers and data scientists to deliver trusted, reusable insights and recommendations.

Hands-on Adobe Customer Journey Analytics (CJA) Lead responsible for designing, configuring, and executing CJA solutions, enabling AEP data flows, defining measurement frameworks, mapping data sources, and delivering reporting while partnering with stakeholders and providing technical architecture and execution.

Manage design, development, and delivery of data products and analytics solutions. Lead and coach an analytics team, gather requirements, improve processes, reduce technical debt, collaborate with platform and product architecture, and ensure solutions meet internal and external client needs.

Lead and build the Risk Analytics function: define pricing methodology and risk frameworks, own portfolio and pricing strategy, convert monitoring into decision systems, architect the Risk Analytics data layer (dbt/Snowflake), mentor senior data scientists, and represent risk recommendations to senior leadership to drive business decisions.

Lead analytics strategy and enterprise semantic/reporting layers across QuickSight/Tableau and Redshift/Athena. Partner with data engineering on domain models, enforce data quality/governance, optimize analytics performance/cost, mentor analysts, and communicate insights to executives.

The role involves building analytics tools and frameworks to support Airbnb's international growth strategy, requiring deep data expertise and collaboration with various teams.

The Senior Analytics Engineer will build and maintain data foundations for corporate reporting, translating business requirements into data models, ensuring consistent metric definitions and investigating data discrepancies for reliable reporting.

Lead analytics for Community Marketing programs: define measurement frameworks, build Power BI dashboards, run analyses across referrals/events/COI, deliver executive insights, forecast leads/opportunities, and partner cross-functionally to optimize program performance and reporting.

Senior AWS Analytics Engineer. Posting contains no detailed responsibilities or qualifications beyond the job title.

Own the Finance & Operations data layer: ingest and model data from systems (NetSuite, Ramp, Pigment) into Snowflake/Omni, ensure data quality and metric governance, build dashboards and reports, collaborate with Finance/Ops stakeholders, and automate reconciliation and reporting workflows.

Lead current-year and long-term AP volume forecasting using statistical and AI/ML methods; diagnose supply-demand drivers; close analytic data gaps; translate analyses into strategic recommendations; mentor staff and communicate forecasts and risks to senior stakeholders across College Board.