Data Analyst Jobs in Tempe, AZ

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.

Partner with business leaders to own core metrics, reporting, and advanced analyses. Build and validate datasets, create executive visualizations, perform driver analysis, time-series forecasting, and apply AI/ML to inform growth and retention strategy. Lead projects, mentor analysts, and support recurring analytic processes.

Partner with business leaders to own core metrics, reporting, and deep-dive analyses. Build and validate complex datasets, perform driver analysis, time-series forecasting and ML solutions, create executive visualizations, manage recurring analytic processes, and mentor analytics teammates.

Design, build, and maintain Power BI reports and dashboards on Microsoft Fabric; create/optimize DAX measures; model data; enforce row- and object-level security; validate data quality; enable self-service datasets; collaborate with stakeholders and use AI tools to accelerate analysis.

Support end-to-end deployment of actuarial pricing in Earnix, perform statistical modeling and data analysis, build dashboards and reports, validate and govern deployments, coordinate releases across environments, monitor production rating behavior, and present findings to stakeholders.

Lead end-to-end analytics for Flagship Client and Distribution: partner with stakeholders to frame problems, perform advanced analyses and machine learning, ensure data quality, develop recurring analytics products and executive visualizations, and mentor analysts to drive data-driven decisions.

Lead budgeting, forecasting, and reporting for non-compensation expenses. Automate expense reporting, administer Prophix financial system, partner with executives to set targets, review monthly performance, and provide financial commentary to drive results.

Collects, organizes, and validates telecommunications and technical data from multiple sources, inputs and reconciles records to meet quality standards, analyzes databases for consistency and patterns, performs data extraction and basic automation, generates reports, and mentors junior staff while adhering to security and ISO 9001:2015 procedures.

Lead quantitative analyses of loan originations and portfolio performance to identify credit risks and improvement opportunities. Build multivariate/predictive models, conduct diagnostic and funnel analyses, measure costs/benefits, design monitoring and controls, present recommendations to VP-level stakeholders, and drive hands-on implementation using SQL, Python, Excel, AI tools, and financial modeling.

Perform reconciliation and data quality controls for advisory accounting, identify and resolve accounting/data issues, validate performance returns, support month-end processes, document procedures, and assist with process improvements and root-cause analysis.

Serve as primary Snowflake administrator and data pipeline engineer: manage Snowflake security, performance, multi-account administration; design and maintain ingestion pipelines and curated data layers; enable AI agents and semantic views; activate/test Snowflake previews; document runbooks and train teams.

Design, build, and maintain production-grade ETL/ELT pipelines and data models using dbt, Spark, and cloud platforms. Manage ingestion, data quality, observability, semantic layers, and BI outputs. Collaborate with analysts and data scientists to deliver governed, high-quality data products and implement DataOps and CI/CD practices.

Serve as a subject-matter expert for client reporting applications: resolve client inquiries and escalations, support 3rd-party reporting and PDR Level II processes, identify trends, suggest operational improvements, and collaborate with internal partners to enhance client experience.

Lead and manage client data contribution, quality, and remediation projects. Coordinate discovery, technical requirements, testing, validation, and production implementations. Monitor and analyze client data, perform root-cause analysis, audit data, provide remediation guidance, and collaborate with internal teams and clients to ensure data quality and ongoing operations.

Manage client data quality and contribution projects for Early Warning products: analyze datasets, develop metrics and reports, coordinate remediation, collaborate with customers and internal teams, and improve data processes and tooling.

Support execution and maintenance of the enterprise risk management program. Lead ERM projects, maintain enterprise risk scorecards, develop annual risk assessment and appetite, design and report KRIs, coordinate RCSAs and GRC updates, produce risk reports and presentations, and record/manage risk data in the GRC system for committee reporting.

Lead data management and quality efforts, consult with stakeholders and vendors, design processes and solutions, perform root-cause analysis of complex data errors, implement improvements, integrate technologies, validate deliverables, and present recommendations to senior management to enable AI-ready data and BI solutions.