Top Remote Analysis Reporting Jobs in Memphis, TN

Leads the design, development, governance, and productization of enterprise data models, pipelines, data products, and ontologies. Builds machine-learning-ready datasets, implements security and lineage controls, optimizes Databricks and Delta Lake environments, establishes data-product standards, collaborates with architects and data scientists, and mentors engineering talent. The role also defines product roadmaps, service levels, usage metrics, and continuous-improvement processes for enterprise data assets supporting AI agents, analytics, and applications.

Build and modify customer reports, perform parcel and transportation analyses, conduct re-rate and carrier RFP modeling, and produce savings and performance reporting. The role pulls and shapes warehouse data, supports business requirements, quality-checks deliverables, documents client interactions, and improves analytical processes. It is a development position requiring advanced Excel, early analytics experience, strong problem-solving, and willingness to learn logistics and parcel industry systems.

Leads marketing measurement and analytics strategy, including Marketing Mix Modeling, Multi-Touch Attribution, experimentation, dashboards, forecasting, and campaign optimization. Manages 8–12 data scientists and analysts, partners with marketing and finance leaders, oversees analytics capabilities and budgets, and presents data-driven recommendations to senior executives.

Owns the CX Operations data foundation in Snowflake by designing architecture, governance, data quality standards, and reusable dbt models. Leads complex analyses, dashboards, scenario planning, and executive communication while mentoring analysts and partnering with engineering and strategy teams. Supports AI enablement by creating trusted data models, evaluation standards, and agent performance tracking.

Build and maintain SQL and dbt data models, tables, views, dictionaries, and self-service tools on BigQuery. Support Accounting, Actuarial, and Claims stakeholders from request through production, monitor data quality, prevent defects, document processes, and review AI-generated code. The role requires hands-on data development, collaboration across projects, and growing ownership of a data domain and stakeholder relationships.

Develop resource allocation, demand forecasting, and capacity models for Customer Success. Analyze quantitative and qualitative data, identify trends and risks, and translate findings into actionable recommendations. Partner with finance, planning, delivery, and leadership stakeholders to refine assumptions, resolve complex business issues, and support regional implementation. Present insights to senior leaders and manage cross-functional priorities in an ambiguous, fast-paced environment.

Administer, maintain, install, configure, upgrade, and troubleshoot IBM DB2 databases across AIX and UNIX environments. Develop SQL, DDL, DML, PL/SQL, shell, and deployment scripts; manage database objects; support releases across development, testing, and production; and provide production troubleshooting to ensure database availability, stability, and reliability.

Build and maintain dbt transformation models and Power BI semantic layers on Microsoft Fabric. Establish data quality testing, observability, governance, CI/CD, documentation, and access controls. Partner with business and technology stakeholders to define reliable metrics and data products, optimize performance and costs, troubleshoot issues, and mentor analysts and engineers while advancing analytics engineering standards.

Analyzes claims data to identify trends, anomalies, root causes, cost drivers, and operational inefficiencies. Partners with claims, quality assurance, SIU, finance, and leadership teams to define analytical requirements, develop recommendations, improve claims handling, reduce risk, and enhance efficiency. Presents actionable findings to technical and non-technical stakeholders, including adjusters, managers, and executives.

Executes actuarial pricing and reserving projects for insurance products using statistical, actuarial, and predictive modeling techniques. Reviews data quality, performs moderate-complexity analyses, supports pricing and product strategies, manages project contributions, documents methodologies, and communicates findings and recommendations to management and business partners.