Top Senior Analysis Reporting Jobs in Phoenix, AZ

Analyzes complex business and system data, writes queries and reports, maintains and monitors applications, troubleshoots issues, and identifies process improvements. Partners with departments and management to evaluate technology needs, implement solutions, document procedures, and lead cross-functional projects. Communicates findings and project status while coordinating priorities, system updates, automation, and core banking software changes.

The Senior Data Analyst leads projects that improve operational performance and client service. Responsibilities include developing business strategies, monitoring operational risk metrics, collecting and presenting performance data, retrieving and optimizing data warehouse queries, mentoring team members in SQL, and communicating findings to operations staff and senior management. The role requires strong analytical, visualization, communication, and project management skills within a financial services environment.

Analyze customer experience and support data using SQL, Python or R, statistical modeling, predictive analytics, machine learning, NLP, and Generative AI. Develop segmentation models, KPI scorecards, and customer satisfaction insights; connect customer metrics to business outcomes and ROI; and communicate recommendations to stakeholders. The role requires 8+ years of analytics experience and supports Reality Labs customer-centric initiatives.

Analyzes and optimizes service and property-turn workflows using SQL, Python, visualization tools, and data-informed methods. Defines metrics, translates business needs into analytical requirements, investigates root causes, evaluates workflow improvements, and partners with business and technical teams on scalable solutions. Presents findings to stakeholders and assesses AI or automation opportunities while considering accuracy, risk, cost, transparency, and human oversight.

Leads long-range workforce and resource planning for contact center operations. Owns demand forecasting, staffing, capacity, headcount, cross-skill, and scenario models across business lines and channels. Develops advanced predictive and prescriptive analytics, performance metrics, and decision-support tools using complex data sets. Advises executives on resource allocation, service levels, costs, and business performance while governing data quality and analytical processes. Leads capacity planning analysts and drives continuous improvement through automation, machine learning, and improved forecasting methodologies.

Leads advanced analytics strategy and delivery, including data preparation, statistical and machine learning model development, experimentation, validation, pricing analysis, and presentation of actionable insights. Partners with business stakeholders to identify opportunities, ensures analytical quality and automation, and builds and manages a high-performing analytics team. Requires leadership experience, advanced quantitative methods, large-scale database work, and proficiency with SQL, SAS, R, Python, and related tools.

Designs trusted Snowflake data products and enterprise semantic models that standardize business concepts, metrics, relationships, and rules. Builds Cortex semantic views and agents, validates AI-generated results, develops regression tests, and maintains metadata, lineage, and documentation. Leads modeling initiatives from discovery through production while partnering with business and technical stakeholders to improve analytics, automation, and AI consistency.

Evaluate claims operational and financial performance, identify trends and root causes, and deliver actionable insights for business decisions. Develop dashboards, scorecards, KPI reporting, and self-service analytics; apply statistical and hypothesis-driven analysis; communicate findings to executive, technical, and operational audiences; and collaborate with data engineering, analytics, actuarial, product, and claims leaders to improve data quality, governance, and reporting repeatability.

Leads competitive intelligence for USAA’s annuity business, analyzing competitors, products, pricing, market trends, filings, and industry developments. Translates insights into strategic recommendations, executive briefings, competitive positioning, and growth initiatives. Manages enterprise-wide research projects, intelligence processes, external agencies, budgets, risk considerations, and a team of analysts. Requires deep annuity and life insurance industry knowledge, strong quantitative and qualitative analysis, executive communication, and leadership skills.

Analyze complex business data to identify trends, risks, and opportunities; build Power BI dashboards, data models, predictive analytics, forecasting tools, and automated reports using SQL and Python. Support inventory optimization, supply-demand balancing, and aftermarket operations while partnering with planning, supply chain, finance, operations, and IT teams. Translate business needs into analytics solutions, present recommendations to stakeholders, and contribute to cross-functional process improvement and business intelligence initiatives.