Top Remote Data & Analytics Jobs in Oklahoma City, OK

Design, develop, and optimize ETL processes, data platforms, and reporting solutions. Lead technical designs, troubleshoot production ETL jobs, support off-hours rotations, collaborate with stakeholders and vendors, and document data processes to ensure scalability, performance, and security.

The Global Head of Pricing will lead pricing functions, optimize margins, develop pricing models, and ensure accurate billing while partnering with multiple teams.

Design and build scalable data foundations, pipelines, semantic models, and AI-grounded tooling. Lead platform-level AE tooling, reusable dbt patterns, observability, cost strategies, and agentic AI workflows. Partner with stakeholders, guide team technical development, and drive cross-functional data initiatives from ambiguous problems to production.

Own and evolve Moxie’s semantic layer (dbt + Omni), build benchmarking and segmentation datasets, enable embedded AI-driven analytics, lead revenue reconciliation and data governance, partner with BizOps to deliver actionable metrics, and lay groundwork for predictive and prescriptive analytics.

Lead and expand the enterprise reporting and BI platform: gather requirements, develop reports and visualizations, write complex T-SQL/stored procedures, ensure SDLC practices, mentor junior developers, and partner with stakeholders to deliver accurate, timely business insights.

Perform full-stack on-chain and product analytics: query on-chain data, profile ecosystem actors, benchmark protocols, define KPIs, build dashboards, and translate findings into actionable briefs for strategy, BD, product, and growth teams.

Design and implement end-to-end Microsoft Fabric data solutions (ingestion, Lakehouse, warehouse, real-time). Create architectures, reusable frameworks, and governance patterns for insurance datasets. Lead ingestion pipelines, optimize performance/cost, integrate with Azure services and security, support regulatory compliance, and provide technical direction to engineering and analytics teams.

Design and implement end-to-end data solutions on Microsoft Fabric and Azure for insurance datasets. Build ingestion pipelines (batch, streaming, API), Lakehouse architectures, and data models. Enforce governance, security, compliance, and cost/performance optimizations while guiding engineers and stakeholders on architectural best practices.

Responsible for data governance and stewardship: maintain data quality and metadata, define and enforce data policies and standards, coordinate with business and technical stakeholders, and support compliance and data lifecycle management.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.

Owner of high-impact data products for corporate clients: design and run QA processes, investigate and resolve complex data quality issues, collaborate with Insights and Engineering, communicate with stakeholders, and identify opportunities to automate and improve workflows while mentoring peers.

Perform advanced quantitative analyses, build and maintain dashboards and automated reports, collaborate across teams to drive data‑driven decisions, lead process improvements, and mentor junior analysts.

Use statistical modeling and data analysis to generate actionable insights that improve loan origination and production. Collaborate cross-functionally to design, test, and implement solutions, build dashboards and visualizations, maintain data integrity, and communicate findings to stakeholders to inform business strategy.

The Senior Quantitative Analyst will analyze marketing performance to drive business strategies, provide insights on campaign metrics, and collaborate with various teams for decision-making processes.

Drive commercial KPIs across Southeast Asia by analyzing performance metrics, delivering insights to senior leadership, guiding sales teams to opportunities, supporting commercial rollouts and ad-hoc campaigns, and collaborating with stakeholders.

Drive process improvement and automation by identifying inefficiencies, developing automations and data pipelines, analyzing KPIs, and designing LLM/ML-enabled solutions in collaboration with AI. Support analytics, SQL/Databricks work, and deliver data-driven insights to improve operational efficiency.