Top Senior Analytics Jobs in Phoenix, AZ

Leads fraud strategy and analytics across lending and card portfolios. Develops, tests, and optimizes fraud detection rules, controls, models, and risk scores; analyzes emerging threats and fraud performance; oversees vendors and technology initiatives; supports product launches; investigates major fraud events; creates dashboards and executive recommendations; and advises business partners on risk, compliance, and portfolio performance.

Leads enterprise internal fraud analytics, monitoring, and response initiatives. Uses SAS and SQL to analyze complex data, develop fraud rules, identify anomalous activity, and design proactive monitoring solutions. Partners with executives, risk teams, audit, and control functions to deliver defensible, well-governed analytics that reduce fraud risk and withstand regulatory scrutiny. Provides subject matter expertise, consultative guidance, and executive-level communication in an ambiguous, high-scrutiny environment.

Own Eve’s go-to-market data models and semantic layer for governed metrics including pipeline, conversion, CAC, win rate, ARR, and bookings. Establish certification frameworks, modeling standards, documentation, alerting, and analytical application patterns across the organization. Partner with Sales, Marketing, Customer Success, and RevOps stakeholders, resolve conflicting metric definitions, enable AI-grounded data tools, review contributions, and mentor analytics engineers.

Build and maintain dbt data models, SQL transformations, ingestion pipelines, orchestration, and Tableau dashboards in support of HR and enterprise analytics. Own data quality, metric standardization, privacy controls, Row-Level Security, documentation, CI/CD, and troubleshooting from source systems through reporting. Partner with stakeholders to define requirements and KPIs, support workforce forecasting, optimize BigQuery performance, and pilot AI-assisted analytics using Google Gemini.

Own marketing measurement from initial engagement through closed-won revenue. Manage cross-channel reporting tied to Salesforce pipeline, tracking across GA4, advertising platforms, SEO, and AI search. Validate multi-touch attribution, analyze marketing experiments, model budget impact, and recommend investment priorities. Present performance insights to marketing and sales leadership across global regions.

Evaluate enterprise data architectures, governance frameworks, integration patterns, ownership models, and data quality practices. Design target-state architectures supporting analytics and AI, define governance operating models, assess data flows, develop quality controls, and create strategic roadmaps and executive recommendations. Collaborate with business and technology stakeholders on data modernization, cloud migration, AI enablement, and enterprise data management initiatives.

Build Deepgram’s governed decision layer above warehouse gold tables. Responsibilities include modeling cross-system entities, owning semantic and metrics definitions, creating agent-facing data tools and MCP surfaces, implementing data quality assertions and reconciliation checks, evaluating AI agent accuracy, and answering business questions while leaving reusable models behind. The role requires production-grade SQL and Python, semantic-layer ownership, strong data modeling judgment, AI-native workflows, clear writing, and comfort building infrastructure from scratch.

Leads enterprise data and analytics strategy, architecture, modernization, and delivery across cloud and on-premises environments. Oversees data platforms, engineering, integration, governance, quality, lineage, security, and compliance. Partners with executives to define roadmaps and investments, manages cross-functional teams and vendors, enables AI/ML capabilities, and mentors data professionals while driving scalable, trusted data solutions and measurable business outcomes.

Manages programmatic analytics and insights for client accounts, leading measurement frameworks, brand lift studies, incrementality testing, and A/B experiments. Develops media and campaign strategies, communicates performance insights to clients, and supports pitches and QBRs. Oversees, mentors, and develops analysts while partnering with Product, Engineering, Sales, and Customer Success teams to improve measurement tools, campaign optimization, and analytical capabilities.

Owns fraud performance analytics for depository products, including monitoring losses, approval rates, false positives, customer friction, and risk metrics. Builds data models, transformation pipelines, dashboards, scorecards, and monitoring frameworks. Conducts fraud deep dives and develops optimized rules, policies, thresholds, models, and decision strategies. Partners with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk teams to improve fraud detection and support product launches.

Leads analytics strategy and technical delivery for clients, specializing in Adobe Analytics and Customer Journey Analytics. Conducts measurement workshops, defines KPI and implementation strategies, oversees tagging and data quality, guides experimentation, and reviews dashboards and insights. Advises senior stakeholders, manages and mentors consultants, supports proposals and account growth, and contributes to Adobe Experience Platform initiatives involving Target, RT-CDP, and AJO.

Lead pricing strategy and origination risk analytics to optimize loan pricing, forecasting, and approval frameworks. Manage and mentor analysts, build quantitative models, integrate third-party data, run experiments, and present recommendations to senior leadership to drive growth and profitability.

Develops and maintains dashboards, reports, scorecards, data models, forecasting solutions, and business intelligence tools. Analyzes complex datasets to identify trends, risks, opportunities, and business drivers, providing actionable recommendations to leaders. Partners with stakeholders to translate business needs into analytical solutions, communicates findings, and improves data integrity, governance, automation, and reporting capabilities. Requires familiarity with banking operations, regulatory compliance, SQL, Excel, Power BI, Tableau, and data visualization.

Performs complex fraud analytics and financial modeling for money movement products. Uses SAS, SQL, Excel, Tableau, and databases to evaluate fraud risk, develop mitigation strategies, improve portfolio performance, and recommend policy changes. Leads reporting, strategy requirements, testing, and rollout activities, supports biometrics enhancements, and helps implement machine learning capabilities while communicating recommendations to senior management.

Leads business analytics strategy, teams, and data-driven decision-making. Oversees dashboards, reporting, advanced analytics, data governance, data quality, and analytics technology roadmaps. Translates business requirements into scalable solutions, ensures data integrity, supports enterprise analytics platforms, and provides strategic insights to executives and stakeholders. Manages competing projects, cross-functional collaboration, and continuous improvement initiatives.

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.

Leads complex private banking data management and analytics initiatives, defining data strategies, quality standards, product attributes, and integrated client views. Partners with business, engineering, analytics, AI, and Wealth teams to translate needs into dashboards, KPIs, predictive models, personalized insights, and intelligent decision-making capabilities. Serves as a subject matter expert on private banking products while mentoring junior team members and enabling platform readiness.

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.

Performs advanced product and business analytics for a consumer mobile app, including experimentation, statistical analysis, metric development, dashboards, and leadership-ready insights. Partners with Product, Engineering, Finance, Data Science, and Analytics teams to guide strategy and feature iteration. Works independently with large datasets, communicates tradeoffs clearly, and uses AI-assisted tools to improve analytical efficiency.

Owns B2B and B2C funnel, enrollment, revenue, and marketing performance reporting. Builds executive and Board dashboards, analyzes CAC, LTV, retention, conversion, spend efficiency, and ROI, and reconciles marketing activity with financial results. Maintains KPI definitions and reporting governance while partnering with Marketing, Finance, FP&A, Sales Operations, and Data teams. Supports strategic planning, diligence requests, and actionable business recommendations through accurate, cross-functional analytics.

Lead insurance risk analytics engagements for property and casualty carriers. Responsibilities include product demonstrations, regulatory filing guidance, pilot and proof-of-concept design, loss ratio and model validation analysis, client project management, discovery sessions, and translating insights for actuarial, underwriting, and executive audiences. The role also develops AI-assisted workflows and provides customer feedback to product teams.

Lead and scale companywide analytics for a DTC marketing business: own marketing measurement, financial forecasting, retention/LTV modeling, data architecture, reporting, and the analytics team. Set analytics strategy, oversee data engineering roadmap, build dashboards, apply statistical and ML methods, and translate insights into executive-level decisions.

Analyzes healthcare claims, provider reimbursement, QPA, and dispute data to support No Surprises Act negotiations, arbitration, and OON liability management. Builds SQL-based reports, dashboards, data processes, and financial views; validates data quality; tracks dispute KPIs; integrates internal and external sources; and presents actionable recommendations to leadership and cross-functional stakeholders.

Analyzes paid media performance across the full funnel, connecting spend and platform metrics to applications, enrollment, student lifetime value, and ROAS. Builds attribution frameworks, Databricks data pipelines, Power BI dashboards, semantic models, and advanced DAX reporting. Supports marketing mix modeling, experimentation, web analytics data quality, forecasting, governance, and workflow automation. Translates complex analytics into strategic recommendations for executive and cross-functional stakeholders.