Top Remote Data & Analytics Jobs in Cleveland, OH

Analyzes claims data to identify trends, patterns, risks, and business opportunities. Retrieves, validates, and prepares data from multiple databases; creates reports, dashboards, visualizations, spreadsheets, and presentations; supports forecasting and reporting needs; collaborates with claims, underwriting, product, IT, and leadership teams; and communicates recommendations for business decisions and process improvements.

Build Python and SQL data pipelines, maintain data integrity, automate dashboards and reporting, and deliver actionable analytics. Develop AI- and LLM-assisted workflows for data enrichment, classification, summarization, and process automation. Support leadership decision-making, sales, customer success, and internal efficiency while communicating insights to nontechnical stakeholders. Evaluate, document, and monitor AI solutions for accuracy, cost, risk, and auditability.

Designs, develops, deploys, and supports complex enterprise data pipelines, data models, ETL/ELT processes, and analytical solutions. Leads data governance engineering initiatives involving metadata catalogs, lineage, data quality, and remediation. Builds governed, AI-ready datasets and integrates AI capabilities into production data workflows while validating performance, security, privacy, and reliability. Collaborates with business, technology, data science, and application teams to deliver scalable, compliant solutions.

Leads Development’s data and systems operations, including CRM and WeGive administration, platform integrations, data hygiene, reporting, governance, troubleshooting, documentation, and staff training. Manages the Constituent Records Management team and Business Solutions Analyst, oversees vendor relationships, validates system updates, supports donor-data security and compliance, and translates technical issues into operational recommendations for leadership.

Leads sales attribution and incrementality measurement for advertising campaigns using transaction data. Develops causal measurement methodologies, productizes client reporting, advises senior brand and agency clients, sets measurement standards, partners with Product and Engineering on automated pipelines, and grows the measurement team. Requires deep advertising analytics, purchase-based measurement, causal inference, SQL, Python or R, and familiarity with retail media, DSPs, clean rooms, and campaign exposure data.

Lead managed services for clients' Azure, Databricks, and Microsoft Fabric data environments. Architect, implement, monitor, troubleshoot, and govern data platforms, ETL pipelines, data warehouses, semantic models, reporting, and AI/ML solutions. Manage incidents and SLAs, advise clients on licensing and technical strategy, communicate solutions, document environments, and mentor distributed engineering teams.

Analyzes data from multiple sources to identify trends, develop member segmentation and lifecycle models, support competitive analysis, and recommend strategies for improving member participation and financial products. Builds reports, dashboards, and data-driven tools for leaders and staff, collaborates with stakeholders, trains power users, and provides ongoing analytical support using SQL, R or Python, ETL, data modeling, and business intelligence tools.

Own the analytics function supporting fraud, credit risk, and operations. Build automation, reporting infrastructure, fraud-rule backtesting frameworks, risk-label systems, dashboards, and AI-assisted tools. Partner with stakeholders to identify high-impact opportunities, reduce manual work, and track hours saved. This hands-on individual contributor role has managerial scope and includes defining a new analytics function.

Design, build, and maintain data lakes, data warehouses, and end-to-end data pipelines for a multi-tenant SaaS platform. Lead code and design reviews, write infrastructure-as-code, optimize performance and scalability, participate in data governance, mentor junior engineers, evaluate new technologies, automate tests, collaborate cross-functionally, and join on-call rotation to ensure reliable data delivery.

Analyze operational data, build and maintain Power BI dashboards, validate data quality, investigate trends and discrepancies, document reporting definitions, and communicate findings to business stakeholders. Partner with IT, data engineering, and analytics teams to resolve data issues and support reliable reporting. Use SQL, Power Query, DAX, Excel, and AI-enabled analytics tools to transform data and inform process improvements.