Top Senior Data & Analytics Jobs in Phoenix, AZ

Owns data governance activities across Compliance, Finance, Risk, and Controls. Responsibilities include maintaining metadata, supporting data quality rules and remediation, coordinating with Data Owners and technology teams, reviewing governance reporting, and ensuring data assets meet documentation, quality, and regulatory requirements.

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.

Analyze complex datasets, develop data models, dashboards, and visualizations, and conduct predictive and statistical analysis for client decision-making. Collaborate with clients to deliver tailored analytics solutions, maintain data integrity, communicate insights through reports and presentations, and support data-driven operational strategies using SAS, Power BI, Tableau, and SQL tools.

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

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.

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.

Lead business-technology alignment for enterprise data solutions: capture and document requirements, map source-to-target data flows, implement data quality rules and dashboards, integrate with the business glossary, automate processes, and create Power BI visualizations to present analytic recommendations.

Builds, tests, validates, and activates marketing audiences across email, web, paid media, and direct mail. Translates requirements into segmentation logic, performs data and consent QA, investigates discrepancies, documents reusable audience standards, and manages workflow commitments. The role also supports analytics projects, statistical modeling, data visualization, customer research, business intelligence, SQL analysis, governance, implementation planning, and stakeholder training while identifying privacy, compliance, platform, and data-quality risks.

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.

Develops and maintains advanced dashboards and data visualizations using BI and visualization tools. Translates business requirements into clear visual solutions, optimizes dashboard performance and usability, collaborates with cross-functional teams, mentors junior developers, and contributes to visualization standards. The role also involves SQL, data modeling, cloud data sources, Snowflake, ETL/ELT concepts, and scalable analytics practices.