Top Data & Analytics Jobs in Oklahoma City, OK

Contribute data analysis, open-source reporting, visual verification, and investigative journalism to projects involving datasets, satellite imagery, maps, charts, interactive graphics, and digital evidence. Collaborate with reporters and editors, scrape and analyze unstructured data, verify photos and videos, and pitch visual stories while meeting rigorous editorial standards and deadlines.

Supports healthcare data analytics and research projects by evaluating diverse datasets, developing statistical models, validating and cross-referencing data, analyzing care and outcome patterns, and communicating findings to nontechnical stakeholders and clients. The role includes learning healthcare data types, SAS programming, research design methods, and quality improvement analytics while collaborating across multiple teams and managing concurrent projects.

Own analytics and reporting initiatives for EDU Partnerships, from defining business questions through delivery and adoption. Build scalable dashboards, reports, data products, and self-service resources; analyze partner health, performance, student engagement, risks, and opportunities; and deliver partner-facing insights. Collaborate with Product, Engineering, Data, Success, Sales, Marketing, Finance, and Support while communicating findings, improving data quality, and enabling stakeholders to make informed decisions.

Own pharmaceutical media performance reporting, analyze marketing data, develop dashboards, identify optimization opportunities, and present actionable insights to clients. Support attribution, test and control analyses, predictive modeling, AI-enhanced reporting, and process improvements. Collaborate with strategy, analytics, media, client services, data science, and technology teams to advance reporting capabilities and data-driven decision-making.

Organize and curate large volumes of raw information: extract key points from transcripts, maintain clean spreadsheets, curate links/resources, tag and categorize content, and follow or propose systems for information structure. Part-time remote role with initial 10 hours/week and potential to grow.

Leads digital and marketing analytics for customer acquisition across multiple lending brands. Owns performance reporting, measurement frameworks, data governance, attribution and marketing effectiveness models, funnel analytics, experimentation, dashboards, and executive insights. Partners with Marketing, Risk, Finance, Operations, Technology, Engineering, and Data teams to optimize conversion, ROI, customer journeys, and data infrastructure. Requires advanced SQL, web analytics, statistical analysis, experimentation, and marketing measurement expertise.

Develop and maintain reports, dashboards, KPIs, and executive insights using SQL, Power BI, and other BI tools. Reconcile operational and financial data, investigate anomalies, ensure reporting quality, and document data models, metadata, governance, and reporting inventories. The role also performs advanced data manipulation, visualization, data storytelling, and analytical recommendations. Fraud and disputes domain knowledge is preferred.

Leads architecture and hands-on development of scalable data pipelines, governed data models, semantic layers, analytics products, and AI workflows. Writes production SQL and Python, establishes engineering standards, mentors engineers, and drives design reviews. Builds agentic and LLM solutions using retrieval and managed AI services while ensuring data quality, observability, reliability, privacy, and regulatory compliance for PHI and genomic data. Partners with stakeholders, platform teams, and governance forums to deliver trustworthy business solutions.

Leads analytics and data engineering for Sales and Revenue Operations. Builds reporting in Looker and Snowflake, manages CRM data flows into cloud warehouses, establishes transformation and modeling layers, and develops forecasts, scoring, churn, and expansion models. Supports territory, quota, pricing, and revenue-truth initiatives while presenting insights to finance and company leadership.

Analyze product, user, transactional, and repayment data to develop risk and underwriting models, reduce losses and fraud, monitor model performance, and guide product and growth strategy. Build Looker dashboards and LookML models, conduct segmentation and experimentation, measure CAC and LTV, and communicate actionable insights to product, engineering, marketing, finance, and leadership.