Top Analytics Jobs in Memphis, TN

Design and maintain scalable dbt data models and ELT pipelines in Snowflake. Architect data foundations to power AI and LLM-enabled workflows, operationalize core SaaS metrics, and build reusable data assets for analytics and activation. Partner cross-functionally to embed analytics into workflows and ensure scalable, secure architecture.

Build and scale secure data lakehouse and warehouse infrastructure supporting analytics, machine learning, clinical AI performance monitoring, and self-service insights. Develop scalable data pipelines, models, orchestration, quality controls, and LLM-enabled analytics tools using heterogeneous clinical and EHR data. Collaborate with engineering, data science, clinical, product, and client success teams to establish trustworthy metrics and technical solutions.

Lead a team delivering product and business analytics for Fetch's commerce and shoppable experiences. Own prioritization, experimentation, measurement, KPI dashboards, and stakeholder-facing insights to inform product, marketing, and commercial decisions. Manage and develop analysts while partnering cross-functionally to ensure data quality, repeatable analyses, and actionable recommendations.

Lead the architecture and development of enterprise analytics models, dbt transformation pipelines, semantic layers, and BI datasets. Apply dimensional modeling, data governance, quality testing, observability, and performance optimization to deliver trusted business data. Partner with executives and cross-functional teams, standardize metrics, improve legacy workflows, support AI/ML integrations, and mentor engineers. Own key domain models and contribute to the analytics platform roadmap as a technical leader.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, campaign reporting, experimentation, and lifecycle analysis. Partners with Marketing and Finance to connect performance metrics to business goals, automate reporting, and generate actionable insights. Builds churn, retention, segmentation, and LTV models while evaluating paid acquisition and customer growth opportunities using SQL, Python, BI tools, marketing platforms, and modern AI-enabled workflows.

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.

Own the analytics data layer by translating stakeholder needs into certified dimensional models, governed metrics, semantic layers, dashboards, and reports. Build with dbt, SQL, Databricks, Power BI, and Airflow while ensuring data quality, observability, reconciliation, documentation, and dependable orchestration. Partner closely with finance, operations, and client-facing teams, automate recurring workflows, and use AI-assisted engineering practices in a fully remote environment.

Leads Navitus’s centralized analytics team, delivering client performance analysis, financial modeling, underwriting support, pricing analysis, competitive intelligence, dashboards, and strategic recommendations. Partners with Sales, Finance, Clinical, Network Strategy, Account Management, and technical teams to support client growth, retention, RFPs, renewals, and market-facing engagements. Establishes data quality and governance standards, improves analytical processes, and mentors team members.

Leads advanced analytics across the organization, owning MAU forecasting and growth models, experimentation standards, and causal inference methods. Establishes analytical best practices, reviews high-stakes analyses, partners with data and product teams, and scales recurring work through AI tooling. Mentors data professionals and translates complex statistical findings into actionable leadership recommendations.

Build executive-facing dashboards, scalable data models, semantic layers, and reporting datasets using dbt, Looker, and SQL. Analyze large datasets, identify trends and anomalies, manage the Looker analytics platform, resolve data quality issues, and deliver analytics initiatives across business domains. Partner with product, engineering, finance, and operations stakeholders to define metrics and reporting solutions. Mentor junior analytics engineers and improve analytics standards and documentation.

Lead Client Legal Services analytics strategy and team development. Own Power BI reporting products, Microsoft Fabric data solutions, governance, predictive modeling, responsible AI adoption, ROI measurement, and executive insights. Partner cross-functionally to improve legal operations, litigation outcomes, staffing, capacity, cost management, quality, and workflow optimization while building scalable analytics capabilities and institutional knowledge.

Complete and document real-world Google Analytics workflows involving reports, traffic, users, events, conversions, audience insights, and engagement metrics. Record screen demonstrations, create prompts and rubrics, explain workflow steps, review outputs for accuracy, and follow project quality standards independently in a remote contract environment.

Lead analytics and data science initiatives to drive measurable business outcomes across various functions, including Underwriting and Claims. Oversee the full analytics lifecycle, foster stakeholder engagement, and mentor junior team members.

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.

As a Revenue Analytics Manager, you will own reporting for Sales, Marketing, and Customer Success, build dashboards, automate workflows, and ensure data quality.

Lead design and implementation of tracking with GTM, analyze user behavior in GA4, build BigQuery queries and dashboards, define KPIs with cross-functional teams, troubleshoot tagging/data issues, and perform deep-dive conversion and journey analyses to optimize web and mobile performance.

Owns executive reporting for autonomous vehicle system performance, including the weekly Software Performance Review and broader commercial readiness analyses. Synthesizes robotics data, diagnostic evaluations, and performance metrics into strategic narratives for senior leadership. The role aligns cross-functional engineering data, automates reporting pipelines and presentation generation, establishes visualization standards, and mentors junior engineers. It requires deep knowledge of robotics, autonomous vehicle performance, data architectures, executive communication, and AI-assisted development workflows.

Build and optimize Hipp’s analytics data platform, including production data pipelines, warehouses, schemas, dashboards, reports, and data models. Write complex SQL, monitor data quality, perform product and operational analysis, and translate business needs into technical solutions. Collaborate with product managers and data scientists to support AI and ML initiatives, deliver reliable insights, and inform product strategy.

Leads commercial analytics and business intelligence strategy, including executive dashboards, account reporting, revenue and pricing analytics, operational KPIs, forecasting, segmentation, and predictive modeling. Partners with Sales, Finance, Marketing, Operations, and Product to improve revenue, profitability, customer retention, and marketplace performance. Presents insights to executives and customers while managing analytics teams, budgets, vendors, and BI scalability.

Own executive, board, investor, financial, and operational reporting for leadership. Build scalable dashboards, define consistent KPIs, reconcile data across systems, investigate performance changes, and translate complex business questions into actionable insights. Partner with Strategy, Finance, and senior leaders to automate recurring reporting, improve data accuracy, and support actuals-versus-budget-versus-forecast analysis.

Build and operate Imagine Worldwide’s AWS- and ClickHouse-based analytics platform, including infrastructure, data lakes, Spark processing, ingestion pipelines, Airflow orchestration, dbt models, CI/CD, monitoring, security, backups, and cost optimization. Process billions of device events and integrate program context into reliable analytical datasets. The role also involves incident response, documentation, architectural contributions, and collaboration with globally distributed analytics and operations teams.

Analyze marketing and customer data to measure campaign impact, uncover customer insights, and improve marketing ROI. Build Tableau dashboards, write and optimize SQL queries, conduct segmentation and lifecycle analysis, validate data quality, and provide actionable recommendations. Partner with marketing, product, and analytics stakeholders to translate business needs into analytical solutions and support strategy across channels, including spend allocation, targeting, attribution, and campaign effectiveness.

Leads marketing and sales analytics strategy, architecture, and measurement. Builds data models, pipelines, machine learning datasets, attribution and incrementality models, and revenue-performance analyses. Advises leaders on investments, tools, account prioritization, and funnel economics. Establishes data, metric, testing, and privacy standards; partners with Marketing, Sales, Finance, Revenue Operations, Data Engineering, and IT; plans roadmaps; presents recommendations to executives; and mentors analysts and engineers.

Leads Marketing's data architecture, metric governance, analytical modeling, predictive modeling, experimentation, and executive performance reporting. Manages three to four analysts while remaining hands-on with advanced SQL, Snowflake data validation, dimensional modeling, cross-system reconciliation, attribution, customer analytics, and AI-assisted natural-language analytics. Partners with engineering, governance, product, and marketing teams to define data products, ensure analytical accuracy, and establish scalable measurement standards.

Build and lead Surescripts’ commercial analytics function, including governed Salesforce and CRM data models, KPI definitions, dashboards, forecasting, pipeline analytics, customer journey insights, automated reporting, quota modeling, and territory planning. Manage an analyst and partner with Sales, Marketing, Finance, Data, and Business Applications. Present actionable recommendations to senior leaders while improving data quality and enabling self-service analytics.