Top Senior Analytics Jobs in Tulsa, OK

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.

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.

Design and deliver reporting, dashboards, and analytics for higher education advancement and constituent data. Gather requirements, define KPIs, perform SQL-based analysis and data validation, and build actionable Tableau visualizations. Advise clients, run workshops, collaborate with data engineering/CRM teams, document business rules and tests, and support adoption and analytics modernization initiatives within a consulting environment.

Own and architect the semantic layer and metrics/metadata for the data platform (Databricks/GCP). Build AI-ready models, enforce modeling and documentation standards, implement observability/testing for pipelines, enable self-serve analytics, and collaborate across product, clinical, and business teams to translate questions into reliable data solutions.

Lead end-to-end strategic projects to optimize health plan programs, perform data-driven analyses, build impact models, present executive recommendations, advise cross-functional stakeholders, mentor junior analysts, and monitor initiative outcomes to improve efficiency and care quality.

Owner of data platform modernization: design and migrate legacy systems to Kimball-style dimensional models and star schemas; build reliable production data pipelines; enforce data hygiene and validation; champion dbt best practices; mentor junior engineers; collaborate with analysts and stakeholders to ensure scalable, well-documented data models and platform observability.

Lead credit underwriting, pricing, verification, and portfolio performance for personal loans. Use data and ML/AI to design automated decisioning, manage credit/fraud risk, forecast losses, and present strategies to leadership and investors. Collaborate cross-functionally and build vendor/alternative-data strategies to drive profitable growth while keeping losses within risk appetite.

Lead development and scaling of financial analytics: build data models, dashboards, and reporting; translate financial data into executive insights; embed predictive analytics; partner with Finance, IT, and business units to improve data quality, governance, forecasting, and automation.

Design, build, and support SAP Analytics Cloud dashboards, planning models, and executive reporting. Integrate SAC with SAP and non‑SAP sources, develop KPIs and forecasting models, run testing and UAT, troubleshoot issues, and support production deployments and stakeholder workshops to deliver actionable analytics for FP&A and operational teams.

Lead the analytics team for the third-party agent business, driving business strategy, product analytics, and AI-powered insights while fostering cross-functional partnerships.

Client-facing Analytics Manager who architects large-scale digital analytics (GA4/Adobe), audits implementations, builds measurement frameworks, and leads GEO (Generative Engine Optimization) test & learn programs. Uses AI tools (Claude) to automate workflows, mentor teammates, manage projects, and translate data into strategic client recommendations.

Lead and scale companywide analytics for a DTC marketing business: own marketing measurement, financial forecasting, retention/LTV modeling, data architecture, reporting, and the analytics team. Set analytics strategy, oversee data engineering roadmap, build dashboards, apply statistical and ML methods, and translate insights into executive-level decisions.

Lead revenue forecasting, planning, and executive reporting across new, renewal, and expansion revenue. Manage and grow a revenue insights team while owning pre-sales analytics, forecast methodology, capacity and quota planning, and performance narratives. Build pipeline and forecast reporting, track conversion/velocity metrics, surface risks early, and apply AI to improve forecasting, anomaly detection, and automated insights.

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 data-driven contact strategy for delinquent customer outreach. Design and run Champion/Challenger tests across email, phone, and digital channels, build segmented outreach schedules, measure channel mix performance, and deliver a roadmap and executive-facing insights to optimize recovery, customer experience, and operational cost tradeoffs.