Top Senior Analytics Jobs in Phoenix, AZ

The Director, Research - Power Markets is responsible for leading the QA/QC process for long-term forecasting, advising leadership, and ensuring market insights are effectively integrated into forecasts.

Lead transformation of Front Line Monitoring from rule-based to AI-driven, owning end-to-end analytics lifecycle, operationalizing AI/LLMs and Copilot-enabled workflows, delivering risk-detection solutions, building an AI-fluent team, and partnering with senior leadership and cross-functional stakeholders to scale monitored, governance-compliant analytics capabilities.

Lead transformation of Front Line Monitoring from rule-based to AI-driven analytics. Own end-to-end model lifecycle, champion AI/LLM tooling, build an AI-fluent analytics team, deliver risk-detection solutions with strong governance, and partner with senior leaders to scale monitoring across the organization.

Lead analytics for Business Banking collections and workout operations: design and monitor credit strategies and models, identify automation and process improvements, translate analytics into operational changes, lead cross-functional teams, drive program rollouts and testing, and provide decision-ready insights to align strategy, operations, and risk.

The analyst will own planning for launches, build forecasting models, partner with stakeholders, and drive data-driven decisions using AI and analytics.

Designs, builds, and operates ELT data pipelines and analytical datasets for Platform Analytics. Curates and models source data into conformed datasets, ensures performance, reliability, and cost efficiency, contributes to target-state architecture, mentors junior engineers, and uses AI coding tools to accelerate development and delivery.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead technical design and architecture for analytics engineering: build and govern the semantic/metrics layer, optimize dbt and Snowflake for performance and AI use cases, mentor engineers, partner with Data Science and Engineering, drive data quality, CI/CD, observability, and deployment of third-party data and emerging tooling to support analytics, ML, and agent-based products.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Lead a team of analysts and data scientists embedded in sales to build rigorous pilot analyses, create executive-ready business cases, expand consultative analytics across the partner lifecycle, and publish industry insights while coaching and scaling the Solutions Analytics function.

This role drives data-driven decision-making in product analytics, collaborating with cross-functional teams to generate actionable insights and evaluate new launches to enhance platform growth.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

The Senior Analytics Engineer will develop data pipelines, build models, and create dashboards to provide actionable insights for various teams. The role requires collaboration with multiple stakeholders to meet analytical needs and ensure data governance.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

The Senior Reporting & Analytics Consultant leads customer-focused reporting and analytics engagements, developing solutions, supporting implementations, and training clients, while ensuring project success.

Senior business-analyst role requiring 8–10 years experience with 3–5 years in IBM Cognos ICM. Must understand Cognos ICM business functionality, have payments and compensation processing domain knowledge, and be proficient with Agile and Waterfall methodologies. Product management experience in ICM sales performance, payments, compensation, BI/analytics is a plus.

Lead Cognos ICM business analysis and architecture for sales performance, payments, and compensation processing. Translate business needs into ICM solution designs, apply Agile and Waterfall methods, and support BI/analytics and product strategy for compensation systems.

Senior business analyst role focused on IBM Cognos ICM. Requires deep Cognos ICM experience, payment and compensation processing domain knowledge, and expertise with Agile and Waterfall delivery. Involves product management exposure for sales performance, payments, BI/analytics, and customer/B2B processes.

The Staff Analytics Engineer will own the Financial Subledger Data Platform, build dbt models, implement data quality controls, and mentor a junior engineer, ensuring high operational reliability and cross-functional collaboration.

Manage and develop a team of data analysts to deliver strategic analytics projects, ensure data accuracy, build reports and dashboards, translate insights into business recommendations, improve operational processes, coordinate cross-functional projects, and support budgeting and team development.

Lead the marketplace analytics by optimizing monetization strategies, monitoring performance, creating dashboards, and analyzing supply-demand dynamics. Collaborate cross-functionally to drive engagement and profitability.

The Data and Analytics Consultant assists clients in data-driven decision making, steering strategic initiatives and transforming data platforms across organizations to enhance business performance.

The VP of Analytics will lead the analytics strategy at AssetMark, overseeing operations, advanced analytics solutions, and team development to enhance client experiences and business performance.