Top Remote Analysis Reporting Jobs in Oklahoma City, OK

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Build and manage HR data pipelines, ETL/ELT processes, data warehouse models, and analytics workflows across cloud platforms. Ensure data quality, governance, security, and availability for People Analytics and HR stakeholders. Lead and mentor data engineers, collaborate with business and IT teams, and support reporting and analysis using tools such as Python, R, and business intelligence platforms.

Develop and manage HR data pipelines, ETL processes, warehouse models, and data transformations for People Analytics. Integrate data from Workday, payroll, talent management, and other systems while ensuring quality, security, governance, and compliance. Mentor data engineers, support reporting workflows in Python and R, and collaborate with HR, IT, and business stakeholders to deliver reliable analytics solutions.

Designs and develops data infrastructure, ETL pipelines, prototypes, and enterprise data assets supporting analytics and Data Science. Partners with business users, data scientists, and analytic engineers to deliver solutions from ideation through implementation. Responsibilities include data exploration, testing, validation, monitoring, predictive-modeling support, data visualization, and functional test execution. Provides technical guidance and mentors team members while promoting innovation and process improvement.

Leads the strategy, architecture, governance, reliability, and evolution of enterprise BI and analytics platforms. Oversees deployment, automation, security, monitoring, disaster recovery, integrations, licensing, vendor relationships, and cost optimization. Enables self-service analytics, leads incident response, and drives continuous improvement. Builds and mentors platform engineering teams, establishes operating models, and communicates platform strategy and performance to executives while partnering across technology, analytics, security, and business functions.

Leads actuarial financial data systems and marts, developing data solutions, extracts, reports, analyses, automations, validations, and executive reporting support. Manages data mart maintenance, audits, business requirements, technical specifications, user acceptance testing, and system implementations. Provides technical leadership, coordinates vendors and departments, trains junior staff, and advises project teams on data architecture, business rules, configuration, and financial data quality.

Analyzes customer loyalty data to generate actionable insights, recommendations, visualizations, and narratives for clients. Builds audience lists, applies segmentation and statistical modeling techniques, develops test plans, and collaborates with CRM, Data Engineering, Business Intelligence, Strategy, and Client Services teams. The role is client-facing and manages request prioritization while supporting loyalty marketing initiatives and measurable business outcomes.

Performs digital measurement analytics for emerging payments platforms, including data collection, validation, reporting, and feature-performance measurement. Partners with marketing, technology, digital, and analytics stakeholders to implement strategic priorities, deliver accurate insights, and support digital data strategy. The role also contributes to analytics roadmaps, project delivery, internal initiatives, and actionable business recommendations using SAS, SQL, Tableau, and Adobe Analytics.

Build and operate a large-scale enterprise data platform spanning batch and streaming processing, lakehouse storage, Kafka infrastructure, APIs, observability, and agentic MCP interfaces. Develop reusable ingestion and data-quality frameworks, improve scalability and resilience, establish engineering practices, support production operations, and mentor engineers. The role requires deep ownership of distributed data infrastructure and practical use of AI coding agents.

Leads decision support and data analysis projects, translating business requirements into reporting applications and analytical solutions. Develops complex programs using SAS, R, SQL, and database technologies; models data sources and flows; creates analytical methods and performance measures; interprets statistical results; and presents recommendations to stakeholders. Mentors colleagues, supports data governance and security frameworks, and consults with internal and external business partners.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.