Top Data & Analytics Jobs in Tulsa, OK

Investigate and analyze suspected fraud cases, monitor and validate fraud strategies, develop countermeasures, evaluate risk scenarios, and collaborate cross-functionally to improve fraud detection and minimize false positives/negatives.

Build data foundations and end-to-end pipelines, research and implement quantitative pricing, market-making, and risk models for prediction markets, model cross-market dependencies and parlays, develop backtesting/simulation frameworks, monitor model performance and collaborate closely with traders to improve pricing and trading outcomes.

Lead a distributed SQL team and own the end-to-end service model for custom analytics: intake, scoping, delivery, QA, documentation, and SLAs. Serve as a customer-facing technical lead, build scalable workflows and request taxonomy, partner cross-functionally, and balance customer delivery with internal platform priorities.

Own and evolve the analytics platform: build and maintain dbt data models, govern semantic metrics in Lightdash, ensure data quality and observability, and partner with analysts and stakeholders to enable reliable self-service reporting.

Lead enterprise data platform strategy and architecture, define data standards and governance, drive Snowflake maturity, oversee legacy data migrations, design ingestion and DataOps patterns, and enable analytics, reporting, AI, and reusable data products across the organization.

Lead development and governance of the supply chain data warehouse and analytics platforms. Build SQL-driven models, dashboards, and KPIs to drive inventory optimization, cost reduction, supplier performance, and working capital improvements. Support ERP integrations and data migrations, perform deep data discovery and predictive analytics, and present actionable insights to senior leaders to enable strategic decision-making.

Own analysis, validation, and documentation of enterprise platform workflows and data inputs. Define test strategies, lead functional/regression validation, approve configuration changes, and drive remediation. Partner with engineering/product to ensure platform reliability, data quality, and release readiness while applying AI-enabled tools to improve efficiency.

Design, build, and maintain ETL/ELT pipelines and data architectures to ingest, normalize, and integrate operational and infrastructure data. Develop API integrations, database queries, and telemetry pipelines; create dashboards and reports; troubleshoot production data quality and collection issues; produce documentation and collaborate with stakeholders to support compliance tracking and operational analytics.

Build and maintain Quince's compensation data environment: integrate HR systems, automate benchmarking and AI workflows, support comp reviews and equity approvals, analyze pay trends, and partner with Talent, Finance, and Legal on global comp strategy.

The Staff Data Engineer will lead financial data operations, ensuring accuracy and reliability of data pipelines, while collaborating with Finance, Product, and Engineering teams to enhance systems and decision-making processes.