Top Remote Analytics Jobs in Phoenix, AZ

Own Toast’s Voice of the Customer program across customer segments, analyzing NPS, CSAT, CES, qualitative feedback, and business metrics. Identify root causes of customer pain, develop data-driven recommendations, improve CX measurement practices, and influence cross-functional teams to prioritize customer-focused solutions. The role also builds listening channels, promotes customer-centric decision-making, and aligns CX priorities with organizational goals.

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.

Leads Toast’s analytics engineering function, owning enterprise data architecture, modeling strategy, analytics-layer development, and AI-ready semantic-layer vision. Builds and manages a team of analytics engineers, establishes roadmaps, partners with data engineering and business leaders, and drives scalable, governed data solutions across domains. Requires expertise in data modeling, dbt, SQL, stakeholder alignment, and people leadership.

Leads analytics initiatives and develops reporting, dashboards, automation, data models, and AI-enabled solutions to support business decisions. Manages priorities, timelines, risks, and stakeholder relationships across projects while coaching an analytics team. Reviews solution quality, guides technical delivery, and identifies opportunities for self-service analytics and process improvement. Requires six or more years of analytics or business intelligence experience, leadership experience, and proficiency with platforms such as Power BI or Tableau.

Leads analytics initiatives and manages a team of analytics professionals while delivering reports, dashboards, automation, data models, and AI-enabled solutions. Partners with stakeholders to define business needs, prioritize projects, manage risks, communicate progress, and drive adoption. Coaches team members, reviews solution quality, and improves efficiency through self-service analytics and modern tools. Requires substantial analytics experience, people or project leadership, and expertise with business intelligence platforms and semantic data models.

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.

Lead programmatic analytics for clients and internal teams by analyzing campaign and model performance, designing tests, developing measurement solutions, recommending optimizations, and presenting actionable insights. Partner with Sales, Customer Success, Product, Engineering, and clients to align marketing strategies, reporting requirements, and optimization efforts with business goals.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

Leads analytics for Pricing and Supply, managing a team of approximately eight analysts. Partners with cross-functional leaders to prioritize analytical work, build dashboards and decision frameworks, improve metric quality, and generate insights into pricing, supplier coverage, marketplace performance, conversion, margin, and customer behavior. Coaches analysts, establishes scalable analytics processes, and collaborates with data engineering teams to improve data models, tooling, and self-service capabilities.

Build and maintain marketing data pipelines connecting Salesforce, Marketo, and cloud data warehouses. Automate campaign reporting, develop SQL datasets and views, improve attribution and data quality, support CRM and marketing automation configuration, and document data models and processes. Use AI tools such as Claude to accelerate analytics workflows while ensuring reporting accuracy. Partner with Marketing Analytics, Demand Generation, and Marketing Operations to support executive-level pipeline reporting.

Lead GTM analytics across performance measurement, channel economics, data governance, forecasting, planning, and executive reporting. Own metric definitions, data standards, analytical priorities, and business requirements while partnering with Marketing, Data Science, Finance, RevOps, and Engineering. Analyze funnel, attribution, CAC, payback, conversion, retention, pipeline, and territory performance, translating findings into investment recommendations and strategic decisions for senior leadership.

Contract Analytics Engineer maintaining Looker and LookML dashboards, reporting, data operations, sales pacing, data QA, vendor workflows, board reporting, forecasting, and planning support during a director’s maternity leave. The role requires strong SQL and Snowflake skills, analytics engineering experience, vendor management, Git/GitHub proficiency, documentation, and independent work in a lean data team.

Supports provider business development through bundled-payment pricing analytics, financial modeling, and strategic analysis. Builds and refines analytical tools and datasets, develops models for new healthcare bundles, supports provider negotiations, and partners with data science and engineering teams on optimization and data infrastructure. Requires healthcare knowledge, quantitative skills, cross-functional collaboration, and the ability to manage multiple priorities in a fast-paced remote startup environment.

Own weekly and monthly sales performance reporting across SPINS, Circana, retailer portals, distributor feeds, and shelf data. Diagnose velocity, distribution, pricing, promotions, and competitive share; identify risks and opportunities; build buyer-facing category and sell-in decks; evaluate promotions and trade ROI; support Costco planning; and develop dashboards and scorecards that turn sales data into actionable insights.

Designs, builds, secures, monitors, and supports scalable data platforms across public and multi-cloud environments. Develops batch and streaming pipelines, ELT processes, data lakes, warehouses, APIs, and integrations with transactional systems. Works with SQL and NoSQL databases and technologies including Spark, Hadoop, Databricks, Snowflake, Kinesis, and Lambda. Leads projects, presents to leadership, collaborates with clients and Scrum teams, troubleshoots issues, and enables analytics and machine learning initiatives.

Provides hands-on technical leadership for data analytics support across enterprise customers. Responsibilities include resolving complex SQL, cloud platform, ELT, data pipeline, data warehouse, and BI issues; optimizing analytics solutions; conducting root cause analysis; reviewing SQL and BI changes; mentoring analysts; automating support processes; and advising customers on Tableau, Power BI, and modern analytics architecture.

Establish and lead the People Analytics function, building trusted workforce data foundations, governance, privacy standards, analytical products, workforce planning capabilities, and AI-enabled decision support. Partner across HR, Finance, IT, and business leadership to deliver executive insights, improve workforce decisions, and scale analytics operations. Recruit and develop the analytics team while ensuring responsible data use, global-local compliance, stakeholder adoption, and alignment with organizational priorities.

Design and implement scalable analytics/data models and dbt pipelines, manage Databricks, build dashboards and BI solutions, partner with business stakeholders, support CRM/marketing analytics, and explore GenAI/ML opportunities to deliver reliable, automated data products.

Consult with financial institutions to analyze consumer credit and loan performance, evaluate underwriting and decision rules, develop data-backed lending recommendations, produce client reports/dashboards, and lead engagements using MeridianLink decisioning platforms and BI tools.

Leads claims analytics by partnering with business leaders, developing reporting and data infrastructure, integrating insurance data, and delivering insights for Claims, Finance, Actuarial, and Underwriting. Creates dashboards and analyses, responds to ad hoc requests, interprets financial and actuarial reporting, and mentors junior analysts. Requires advanced SQL, BI, Power BI, and insurance industry expertise.

Build and own commercial data models in Snowflake and dbt for ARR, bookings, pipeline, account scoring, ICP fit, upsell, and whitespace analysis. Establish semantic layers, governance, documentation, testing, monitoring, and CI/CD practices. Partner with Sales, Marketing, Finance, and enterprise data teams to deliver trusted self-service analytics, improve data infrastructure, and develop AI-powered automation. This senior individual contributor will own the roadmap and mentor analysts on data modeling and dbt.