Top Data & Analytics Jobs in Cleveland, OH

Lead design and implementation of a global product master data management solution using Oracle Product Hub. Configure PIM, integrate Product Hub with Oracle EBS and non-EBS systems via middleware, and drive execution with client IT teams.

Leads legacy data migration into SaaS platforms by assessing sources, designing conversion strategies, executing ETL workflows, mapping and transforming data, validating integrity, and managing PII. Engages clients to gather requirements, document business processes, support governance and data quality, coordinate implementation teams, and develop reusable methodologies and training materials.

Develop and optimize enterprise Oracle SQL and PL/SQL solutions, including data models, database designs, APIs, ETL processes, batch jobs, and performance tuning. Collaborate with cross-functional teams to translate requirements into scalable implementations, support testing and CI/CD, troubleshoot production issues, and document solutions. Provide technical leadership, mentor engineers, participate in architecture and code reviews, and drive engineering best practices across data modernization initiatives.

Own data quality across systems by designing validation rules, reconciliation processes, profiling workflows, and quality controls. Investigate discrepancies to identify root causes, apply statistical methods to detect anomalies, evaluate machine learning model outputs, and communicate findings to technical and non-technical stakeholders. Partner with engineering, BI, and business teams to establish data quality standards, metrics, controls, and reporting practices.

Analyze and model property catastrophe reinsurance treaties using catastrophe modeling platforms. Prepare and validate exposure data, execute models, interpret risk metrics, develop scenarios, and identify portfolio risk drivers. Support underwriting, actuarial pricing, placement, renewals, and management decisions through clear reporting. Participate in model validation, calibration, research, and development while collaborating with underwriters, actuaries, and other stakeholders.

Create and validate complex datasets for AI benchmark tasks, including files with malformed records, missing data, truncations, and inconsistent formatting. Define correct final states, write detailed grading rubrics, and assess AI outputs for accuracy and completeness. The role requires exceptional attention to detail, error detection, format reconciliation, accurate documentation, and clear asynchronous communication in regulated or audit-sensitive contexts.

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Senior technical and business leader who defines analytics vision and architecture, builds scalable cloud data platforms and pipelines, drives AI/ML and self-service analytics, ensures governance and HIPAA compliance, and leads a multidisciplinary analytics team to deliver executive dashboards and data products that improve physician and revenue-cycle performance.

Own board-grade analytics deliverables for client engagements by transforming Salesforce pipeline data and BI outputs into executive narratives, presentations, and reusable reporting templates. Analyze pipeline, funnel, and revenue performance; explain variance; write causal commentary; present findings to PE sponsors and executives; and train client teams to maintain deliverables independently.

Design, develop, and optimize scalable Databricks data pipelines using PySpark, SQL, Spark, and Delta Lake. Build workflows, ingestion and transformation processes, data quality checks, monitoring, and CI/CD automation. Optimize distributed workloads, configure Databricks compute, support cloud governance and access controls, troubleshoot production issues, and collaborate with technical and research stakeholders to deliver secure, reliable analytical datasets.

Lead a remote analytics team to deliver dashboards, data products, and decision-support tools. Oversee project plans, stakeholder engagement, data platform modernization, ETL/automation, Tableau/Power BI deployments, statistical modeling, QA, metadata, and staff mentoring to support federal social service programs.

Own enterprise data governance, metadata, lineage, data quality, master data, GxP readiness, cloud data-layer standards, commercial data controls, partner data exchanges, and AI data governance. Lead federated stewardship, executive scorecards, architecture reviews, access models, vendor data governance, and regulatory readiness across clinical, commercial, and corporate data. Partner with Security, Legal, Privacy, Compliance, and QA while building accountable business ownership and trustworthy, rapidly accessible data.

Build and maintain modern data-centric applications, pipelines, transformations, enrichment processes, provisioning layers, and user interfaces supporting clinical and operational healthcare processes. Analyze clinical data and report trends using cloud, big data, data science, and modern software development practices. Collaborate with Product, Platform, and Architecture teams, mentor Data Engineers, document solutions, manage source control, and research emerging technologies.