Top Data & Analytics Jobs

Leads enterprise stakeholder voice and feedback programs, including student, faculty, and course evaluations. Designs qualitative and quantitative research approaches, synthesizes feedback into actionable insights, and develops executive communications, reports, dashboards, and visualizations. Partners with university leaders and cross-functional teams to support evidence-based planning, continuous improvement, governance, and institutional effectiveness. Requires strong stakeholder engagement, facilitation, analytical, presentation, and research capabilities.

Freelance Data Analyst supporting Sprinklr implementation projects through dashboard development, Boolean query and topic creation, reporting, tagging, workflow configuration, quality assurance, and social listening analysis. The role requires strong knowledge of social media metrics, sentiment analysis, digital analytics, and reporting tools, along with independent remote work, documentation, and deadline management.

Supports payer-related platform operations through SQL-based data analysis, reporting, validation, reconciliation, issue tracking, and documentation. Partners with cross-functional stakeholders to investigate operational issues, communicate updates, monitor workflows, and improve processes. Uses Excel, Jira, cloud data platforms, and AI tools to manage requests, summarize findings, support testing, and maintain accurate operational records.

Lead recurring operational reporting and data processes for finance and HR, owning month-end and year-end close activities. Read, analyze, and correct complex SQL (views, stored procedures), maintain BI reports (Power BI, Cognos, Crystal), validate data, trace root causes to source systems, and produce confidential leadership deliverables. Automate recurring work, document processes, and support report modernization and ad hoc analysis.

Analyzes complex business processes, data requirements, and information systems supporting the Defense Logistics Agency. Applies DoD Business Enterprise Architecture, data modeling, enterprise architecture, systems integration, and process analysis expertise to improve data quality, interoperability, modernization, and enterprise decision-making. This fully remote role requires Secret clearance and supports AMPS program initiatives.

Design and implement continuous enterprise risk-control monitoring across credit, fraud, operational, and compliance domains. Develop AI agents, anomaly detection, root-cause analysis, predictive models, and risk-mitigation tools. Maintain AI and model-risk inventories, build dashboards tracking key risk indicators, and communicate analytical insights to senior stakeholders. Collaborate with Engineering, Data, Compliance, Operations, Identity, and Product teams to instrument risk telemetry and maintain human oversight of automated outputs.

Cleans, analyzes, validates, and reports HIV program data from CAREWare, EvaluationWeb, surveillance, testing, prevention, and other sources. Develops data quality checks, resolves inconsistencies, matches datasets, supports reporting and quality management, provides technical assistance to subrecipients, troubleshoots data systems, and translates findings into actionable recommendations for public health leadership and programs.

Supports M&A acquisition integrations by collecting, cleaning, normalizing, validating, reconciling, and mapping seller data into Quench systems. Coordinates with sellers and internal teams to resolve data issues, maintain readiness trackers, prepare cutover materials, and verify migrated customer, billing, service, route, asset, and pricing data. Develops reporting and dashboards while partnering with IT on AI-enabled data intake, validation, exception management, workflow summarization, and process improvement. The role offers progression toward integration leadership within 12–18 months.

Analyze healthcare claims, authorization, and related data to identify trends and opportunities. Develop dashboards, visualizations, analyses, and presentations supporting operational, clinical, and financial decisions. Collaborate with stakeholders, data and engineering teams to define requirements, improve data quality, and deliver actionable recommendations across multiple analytical projects.

Own analytics for Customer Success and Operations by translating ambiguous business questions into metrics, reports, dashboards, and PRDs. Partner with senior leaders, CSMs, Analytics Engineers, and Operations teams to improve retention, permit turnaround, and organizational scalability. Build self-service dashboards, develop dbt models, document analytics assets, prioritize high-impact requests, and use LLM tools to accelerate SQL, reporting, and data-model development.