Top Remote Data Analyst Jobs

Develop and maintain healthcare databases and BI applications, perform reporting and SQL/Snowflake analysis, create dashboards, support ETL/data migration and governance, coordinate testing and vendor/IT integrations, and provide technical training and documentation to support clinical, operational, quality, and billing analytics.

Lead analytics workstreams for commercial payments fraud detection and operations. Translate business needs into scalable analytics, build dashboards and data products, evaluate and optimize models/rules, automate reporting pipelines, and deliver actionable insights to reduce fraud losses and improve operational effectiveness across stakeholders.

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

Lead data analyst responsible for advanced analytics, real-time performance dashboards, network capacity modeling, and generating actionable insights for third-party service providers. Drives testing and pilots, analyzes stakeholder feedback, and serves as an internal analytics subject-matter expert to inform network strategy and operational improvements.

The Data Analyst will generate client reporting using Python and SQL, maintain reporting scripts, conduct quality checks, and enhance data quality for performance analysis.

The Staff Data Analyst will lead data strategy for Compliance, analyzing regulatory engagements, and driving effectiveness through actionable insights and collaboration across various teams.

Design and build scalable data solutions for high-volume transaction streams. Partner with product and business teams to deliver analytics, dashboards, and insights. Lead data strategy, architecture, governance, quality, lineage, and access controls. Enable self-service capabilities and explore new open-source technologies to support business intelligence and operational needs.

The role involves improving transaction monitoring rules, analyzing risk patterns, and building dashboards for compliance while collaborating with investigations and compliance leadership.

Lead data strategy and analytics for Compliance and AML, develop ETL and validations, quantify regulatory risk, communicate insights to stakeholders and regulators, and drive cross-functional compliance initiatives.

Support Finance and Sales by reconciling and validating revenue KPIs (ACV, ARR, renewals), building reporting datasets and dashboards, collaborating with CRM and data engineering teams, and participating in month-end and quarter-end close activities. Provide ad-hoc analysis and stakeholder-facing explanations of metric derivation and data quality.

Lead data strategy and analytics for Compliance, focusing on Financial Crimes/AML. Drive ETL, source validation, and analyses to quantify compliance risk, support regulatory engagements, and influence product and compliance roadmaps. Communicate insights through visualization and cross-functional collaboration while leading multiple high-impact workstreams.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Perform structured data conversion, cleansing, validation, and mapping for system implementations. Execute validation scripts, support UAT, document discrepancies, reconcile legacy and converted data, and escalate anomalies to senior consultants while maintaining organized records and templates.

Support teams in preparing and maintaining AI-ready data by assessing data readiness, improving data quality and metadata, documenting lineage and ownership, and advising on governance and retrieval suitability for AI systems. Collaborate with data engineering, AI, and governance teams to create checklists, guidance, and remediation recommendations without owning pipelines or technical implementations.

Support federal clients by analyzing data, building dashboards and reports in Tableau/Power BI, performing cost and strategic modeling, aiding POM and ICE processes, improving business processes, managing records and compliance, and producing training and program analytics.

Analyze, integrate, clean, and model operational and technical data to produce dashboards, reports, and forecasts. Identify trends, lifecycle/status, risks, and noncompliant assets; support automation, data quality improvements, and decision-making across engineering and operations teams.

Analyze and preprocess Army operational datasets, perform geospatial and exploratory analysis, develop dashboards and reports, apply machine learning and statistical models, and communicate insights to Army leadership.

Own RevOps data models and BI infrastructure to drive GTM strategy. Clean and analyze datasets, build predictive models, define and track leading/lagging KPIs, deploy dashboards, document data definitions, and deliver executive-ready insights while partnering cross-functionally with Finance and GTM teams.

Own and build the support reporting layer: ticket volume, SLA, resolution times, CSAT/CES/sentiment, and capacity. Produce dashboards and analyses for leadership and engineering, maintain data quality and governance, prioritize issues using multi-signal models, and surface Voice of Customer trends to close the loop with Product and GTM.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Analyze C&DS project data to produce reports, visualizations, and predictive/prescriptive models. Build data pipelines and models, mine complex datasets, support data governance, collaborate with IT and stakeholders, respond to ad-hoc requests, and improve business processes using BI tools and statistical methods.

Lead requirements gathering, document functional specifications, review data models, validate implementations, support production deployments, investigate data quality and collaborate with technology teams to ensure data completeness and lineage.

Collect, consolidate, and validate data from disparate sources; document functional specifications; review data models; gather business requirements; support deployments; investigate data quality and bridge gaps with technology teams.

Analyze and consolidate disparate data sources, document functional and business specifications, review data models, validate implementations, support production deployment, and investigate data quality and lineage issues.

Support marketing analytics by analyzing digital channel performance, building and maintaining KPI dashboards, ensuring data accuracy, and collaborating with cross-functional teams to turn insights into actionable recommendations.