Top Senior Analytics Jobs in Tulsa, OK

Lead design and implementation of scalable data models and analytical tooling for Consumer Product. Partner cross-functionally to translate business needs into reliable SQL/Python data products, dashboards, and automated pipelines using engineering best practices (CI/CD, testing, version control, monitoring). Drive data-informed strategy and manage long-term infrastructure while supporting ad hoc requests.

Lead post-sales and revenue analytics by integrating product telemetry, support signals, and revenue data. Build scalable data models, reusable datasets, and semantic layers. Define SaaS metrics, forecast revenue and usage, predict expansion and churn, and deliver dashboards and insights to drive renewals, expansion, and revenue growth.

Lead an analytics implementation for Valvoline's Global Products segment, driving metrics standardization, reporting consistency, and data accessibility. Create a scalable data framework, improve decision-making through visual analytics, and coach internal teams on analytics best practices.

The role involves leading analytics solutions for Valvoline's Global Products segment, implementing a comprehensive data framework, and enabling insights through effective visualization and analytics practices.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

Lead the design and implementation of algorithmic trading strategies, oversee technical infrastructures, and mentor a multidisciplinary team while managing performance analysis and risk.

The Senior Analytics Engineering Manager will oversee analytics engineering vision, manage a team, ensure data quality, and drive data-driven decisions across departments.

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

Lead design, development, and migration of enterprise SAP BW solutions to SAP Datasphere; architect hybrid data flows with Microsoft Fabric and Azure Synapse; integrate BW with Salesforce and SQL Server; embed AI (Copilot, Azure OpenAI) into analytics; manage deliverables, mentor offshore teams, enforce standards, and ensure data integrity and performance for reporting and analytics.

Lead design, development, and migration of enterprise data warehouse solutions from SAP BW/BW4HANA to SAP Datasphere. Architect data models and hybrid data flows with Microsoft Fabric/Azure Synapse, integrate BW with Salesforce and SQL Server, embed AI capabilities (Copilot, Azure OpenAI), manage offshore teams, enforce standards, and deliver Power BI reporting and analytics to business stakeholders.

Execute underwriting and case-valuation analytics: write and optimize SQL, build dashboards, maintain valuation models, forecast case outcomes, monitor portfolio performance, and translate insights for operational and marketing stakeholders.

As an Analytics Engineer, transform raw data into metrics, manage data pipelines, ensure data integrity, and collaborate with teams for analytics solutions.

The Analytics Lead will guide data-driven decision-making, develop measurement frameworks, forecast revenue, and mentor an analytics team, ensuring effective communication of insights.

Lead Oracle Cloud reporting initiatives, ensuring data accuracy and performance while mentoring junior analysts and collaborating with stakeholders.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

The Senior Data Scientist will build frameworks for data-driven decision making, develop predictive models, ensure data quality, and enhance customer experiences through analytics and operational insights.

Lead architecture and execution of Grafana's marketing data stack and analytics practice. Build forecasting, predictive, and causal models, design BigQuery schemas, deploy agentic AI and automated pipelines, partner with GTM leadership, and deliver executive-grade insights to drive demand generation and ROI.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.