Top Remote Senior Data Analyst Jobs

Evaluate and profile data from legacy and disparate systems to assess quality, completeness, and consistency; identify gaps and anomalies; recommend remediation and readiness actions for system modernization and migration; document findings; and collaborate with technical and program stakeholders to improve data usability for reporting and analytics.

Lead and support actuarial data projects: investigate and extract data, validate reports, address data quality, modify SQL/SAS/4GL programs, produce tabular/graphical outputs, communicate results, coach team members, and participate in project leadership and data-system decisions.

Lead research and thought leadership on data management and AI readiness, produce actionable insights, advise clients and sales, present at events, mentor analysts, and improve research processes to drive client outcomes.

Lead data governance for a major enterprise platform migration: liaise with stakeholders, profile and map data, define standards and business rules, validate ETL/MDM mappings, document metadata and lineage, and support data quality and governance processes throughout migration and post-implementation.

The Senior Marketing Data Analyst will analyze customer behavior, optimize marketing spend, and develop actionable strategies while managing the marketing data infrastructure and producing insights for decision-making.

The role involves programming and data review for real-world data analysis, supporting epidemiologists, and managing complex data sets using statistical programming languages and tools.

Support AI, analytics, and data modernization for VA research: perform ETL, statistical programming, reporting, dashboards, LLM-enabled analytics, data integration, quality validation, and executive-level presentations to improve operational decision-making.

Lead data quality and analytics for VA EHRM deployments by building and validating pipelines, applying SQL/R/Python and NLP/ML, defining governance rules in Purview/Collibra, certifying dashboards (Tableau/Power BI), and delivering actionable visualizations and insights to executive stakeholders.

Lead client-facing analytics engagements: translate ambiguous business questions into data models, dashboards, and KPIs; write production-quality SQL and dbt models; build BI reporting; apply AI tools to accelerate analysis; drive proactive insights; set stakeholder cadence; and mentor junior analysts to ensure adoption and delivery.

Perform senior-level analysis on complex healthcare and business datasets (claims, utilization, financials). Design and maintain reports, dashboards, and ETL processes with SQL/SSRS/Excel; ensure data quality; build forecasts and models; lead projects; present insights to stakeholders; support audits and regulatory requests.

Ensure integrity and governance of reporting databases; develop automation frameworks and ETL processes; prepare data for BI; conduct code and periodic reviews; create data policies and documentation; collaborate with stakeholders to enforce data management practices; perform data, gap, and root-cause analysis; maintain performance and adopt new technologies.

Analyze healthcare provider data and business processes, identify improvements, and develop solutions. Serve as liaison between business and IT, lead cross-functional projects, produce presentations and insights, and provide end-user training and support to ensure adoption of new processes and tools.

Leads complex data analysis and designs reporting and data solutions across healthcare domains (claims, utilization, cost). Builds and maintains SQL-based ETL, reports, dashboards (SSRS/BI), ensures data quality, and delivers forecasts and recommendations. Partners with stakeholders, documents processes, supports audits, and drives process improvements and automation.

Provide first-line technology risk oversight for customized data platforms and AI/ML enablement. Identify, assess, document, and help mitigate technology, data, security, stability, third-party, and AI-related risks. Support RCSA, control reviews, issue management, AI use-case triage, stakeholder reporting, and remediation coordination across hybrid-cloud and on-prem environments.

Lead analytics to improve player experience, engagement, retention, and monetization. Analyze player lifecycle, run cohort and funnel analyses, design and evaluate A/B tests, build dashboards, define product metrics, investigate KPI changes, and partner with product, marketing, engineering, and data teams to deliver data-driven recommendations and improve data quality.

Senior data processing analyst responsible for end-to-end survey data processing: specifications, weighting, QA, documentation and deliverables. Produce datasets and tables, perform statistical tests, and modernise/automate workflows (Python/R, replace SPSS). Apply AI-assisted tools, act as technical lead for projects, and mentor junior analysts.

The Data Analyst will conduct full lifecycle analysis, develop reporting capabilities, monitor performance, and identify improvements in data quality and efficiency.

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.

Senior Business Analyst specializing in advanced data visualization: create dashboards, choose optimal chart types for varied audiences, visualize high-dimensional data, apply statistics and financial modeling, collaborate with UX, and help drive execution.

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.

The Data Analyst will analyze marketing and ecommerce data, build reporting, dashboards, and KPIs, and enhance marketing attribution modeling.

The Data Analyst will optimize marketing funnel metrics, conduct analyses, manage dashboards, and promote data-driven decision-making within the team.