Top Remote Data & Analytics Jobs in Cleveland, OH

Develop and maintain ServiceNow reports, dashboards, performance analytics, data extracts, and Power BI executive reporting. Build data models, KPIs, measures, and visualizations for operational performance, compliance, service health, and engineering effectiveness. Automate reporting, data collection, validation, distribution, and notifications using Power Automate, PowerShell, Python, or similar tools. Support Workspace ONE, Intune, macOS troubleshooting, monitoring, endpoint compliance, incident resolution, documentation, and change management.

Lead the architecture and development of Penn Foster Group’s Databricks-based cloud data platform. Build scalable batch, streaming, CDC, and API pipelines using Python, SQL, Spark, and Azure; establish engineering standards, governance, observability, and CI/CD practices; develop AI-ready semantic data products; and mentor data engineers. Partner with BI, product, security, governance, and MLOps teams to support analytics, machine learning, generative AI, and self-service reporting.

Supports analytics product improvements by researching data issues, designing reports, documenting business requirements, developing use cases, and conducting user acceptance testing. The role creates training materials, facilitates user training, supports credit unions and internal users, promotes business intelligence practices, and helps transition analytics solutions into business operations.

Leads business intelligence, workflow automation, and data stewardship for financial risk operations. Builds governed Tableau and Power BI reporting environments, develops Python, SQL, RPA, and ETL solutions, analyzes trends, and delivers predictive insights. Maintains audit-ready controls, data integrity, version management, error handling, and compliance. Partners with stakeholders to modernize manual processes, improve efficiency, track operational performance, and scale self-service analytics.

Leads marketing and enrollment analytics across acquisition and conversion funnels. Analyzes channel performance, ROI, attribution, forecasting, experimentation, and marketing mix modeling; develops recommendations for budget allocation and performance improvement. Uses Power BI, SQL, Python or R, and institutional and marketing datasets to build models, automate monitoring, identify anomalies, and support cross-functional decisions. Owns marketing measurement standards, data quality, tracking, and analytical roadmap while partnering with Marketing, Enrollment, Field, and Institutional Analytics teams.

Develops acquisition fraud analytics and strategies for home and auto platforms. Responsibilities include building analytic solutions, creating automated reports and performance summaries, conducting impact analyses, analyzing client and population data, and tracking champion/challenger strategy tests. The role partners with cross-functional stakeholders, presents insights to senior leadership, and supports credit and fraud initiatives using SAS, SQL, Unix, Excel, and VBA.

Analyze banking and financial crime data, develop and tune statistical and machine learning classification models, evaluate model performance, identify data quality issues, and recommend optimization strategies. The role uses Python and SQL for feature engineering, statistical modeling, automation, and large-scale data processing. Responsibilities also include documenting methodologies, reporting results to management and regulators, and collaborating with compliance, technology, business, and model governance teams.

Senior Decision Scientist partners with product, engineering, marketing, and finance teams to guide roadmaps, resource allocation, and business strategy. The role uses experimentation, causal inference, statistical analysis, metric strategy, and user behavior research to produce actionable recommendations. Responsibilities include establishing causality, improving instrumentation, communicating insights to leadership, and using AI tooling to scale analytical workflows. The position requires consumer technology analytics experience, strong SQL and Python or R skills, and expertise in experimentation and causal inference.

Designs and leads enterprise data pipelines and integrations across Snowflake, Oracle Fusion, on-premises databases, and cloud applications. Ensures data quality, governance, security, scalability, and performance while supporting Power BI, AI/ML, and self-service analytics. Partners with business and technical stakeholders, leads migrations, mentors engineers, optimizes data platforms, and establishes engineering best practices.

Designs, builds, deploys, and maintains scalable data pipelines, data lake systems, batch and streaming processing, MLOps frameworks, data documentation tooling, and an agentic data exploration platform. The role supports customer-facing products and enables engineering teams through reliable infrastructure, observability, data discovery, and AI capabilities.