Top Senior Data & Analytics Jobs in Phoenix, AZ

Own business intelligence and strategic analytics for Avail by analyzing complex data, developing KPIs, building automated dashboards and reports, conducting market and performance analyses, and delivering insights for strategy, product, marketing, operations, forecasting, and revenue growth. The role partners with stakeholders and data engineering to create analytical data layers and self-service solutions that support data-driven decisions.

Lead architecture and delivery of end-to-end Master Data Management (MDM) solutions, manage client engagements and teams, align MDM implementations with business objectives, mentor staff, and maintain quality and governance across data operations and stewardship.

Lead analytics work to develop, validate, and implement pricing loss assumptions for auto lending. Build and enhance statistical models, analyze large datasets, monitor portfolio loss performance, and provide actionable recommendations to Pricing, Risk, Finance, and senior leadership to optimize profitability and ensure regulatory compliance.

Lead analytical work to monitor loan portfolio and originations, detect credit and underwriting issues, build multivariate statistical models, analyze funnels, quantify costs/benefits, present recommendations to executives, design monitoring and controls, and drive implementation using SQL, Python, Excel, AI tools, and financial/statistical techniques.

Develops and maintains advanced dashboards and reporting solutions, analyzes complex datasets, identifies trends and anomalies, and delivers actionable recommendations to stakeholders and senior management. Translates business questions into analytical tasks, ensures data accuracy through validation and quality checks, supports data governance, automates reporting processes, and collaborates with IT to improve data infrastructure and accessibility.

Design and implement data harmonization, ingestion, and visualization for enterprise marketing analytics using Salesforce Datorama (MCI). Build ETL/API integrations and data models, configure advanced metrics and dashboards, enforce data governance, and manage QA and release processes to ensure accurate, high-performance marketing insights.

Leads the strategic direction of performance analytics and measurement for global enablement efforts. Owns the analytics roadmap, defines KPIs, develops AI-driven seller-readiness assessments, and partners with data engineering, sales, enablement, and technology teams. Translates complex analysis into executive-level insights, drives cross-functional alignment, and leads strategic measurement initiatives.

Designs, develops, and maintains enterprise Tableau dashboards and business intelligence solutions. Partners with stakeholders, data engineers, and architects to define KPIs, build trusted data sources, optimize performance, apply governance and security, and deliver intuitive analytics. Supports Tableau Server or Cloud publishing, permissions, troubleshooting, documentation, and user enablement while ensuring consistent metrics and high-quality executive insights.

Leads complex fraud analytics initiatives, including detection development, back-testing, optimization, monitoring, trend analysis, and incident support. Builds executive dashboards and reporting, establishes data quality and performance controls, documents methodologies, and translates findings into actionable recommendations. Provides technical direction, reviews analyst work, coaches peers, and partners with investigative, risk, and technology teams on fraud detection and data modernization.

Analyzes fraud and account takeover risks using SQL, SAS, Excel, Tableau, and relational databases. Develops and maintains fraud detection rules, mitigation controls, monitoring processes, performance reports, and segmentation strategies. Investigates major fraud losses and emerging trends, identifies root causes, recommends policy improvements, and provides actionable insights to cross-functional stakeholders and senior management. The role focuses on minimizing fraud losses while reducing customer friction and improving operational performance.