Top Remote Senior Data Analyst Jobs

Own analytical projects supporting revenue, profitability, and operational performance for the insurance business. Analyze funnels, campaigns, conversions, costs, and trends; build SQL queries and Looker dashboards; automate reporting with Python; define KPIs; validate data; and present actionable recommendations to stakeholders and leadership.

The Senior Data Analyst will lead metrics definition, reporting, statistical analysis, experimentation, dashboard management, and pricing analytics. The role involves building data pipelines, collaborating with data engineers on data assets and feature stores, investigating complex business questions, and translating analytical findings into strategic recommendations for product, pricing, and senior leadership. Strong SQL, statistics, econometrics, communication, and cross-functional collaboration skills are essential.

Analyzes claims data to identify performance variances, operational improvements, and business trends. Develops complex reports and analytics tools across multiple lines of business, quantifies impacts on loss results, responds to urgent requests, and communicates findings to internal partners and senior leaders. Requires strong exploratory data analysis, insurance industry knowledge, Excel and SQL expertise, and the ability to translate complex data into actionable insights.

Analyze complex data to support business decisions across marketing, finance, product, sales, medical affairs, and customer success. Responsibilities include defining data requirements, developing and automating data pipelines, building interactive dashboards, identifying trends and process improvements, and presenting insights to executives and external partners. The role requires advanced SQL, Python, BI, visualization, and cross-functional analytics experience, with an emphasis on using AI to improve efficiency.

Develop customer analytics that improve retention, growth, adoption, and operational performance. Build and maintain BI dashboards, customer health metrics, churn-risk reporting, and predictive models. Partner with Client Success, Product, Sales, and Operations to translate complex findings into actionable recommendations. The role also owns data quality, governance, reporting automation, workflow improvements, and stakeholder communication.

Own end-to-end analytics for subscription products and web funnels, including KPI definition, dashboards, funnel and cohort analysis, payment performance, user behavior, experimentation, and anomaly monitoring. Build reliable SQL data models and maintain event taxonomies and tracking. Partner cross-functionally with Product, Marketing, Engineering, Finance, and BI to improve conversion, retention, revenue, and LTV. Mentor analysts and communicate actionable recommendations to stakeholders.

Own monetization analytics across mobile apps and web properties, including subscription, advertising, in-app purchase, and partner-offer revenue. Build reliable datasets and pipelines, manage revenue metrics, analyze pricing and paywall experiments, model LTV and cohorts, evaluate ad monetization, reconcile revenue sources, and support forecasting and prioritization. Communicate insights to Monetization, Product, and business leaders to drive revenue growth and measurable impact.

Own user acquisition analytics across mobile apps and web properties, measuring channel performance, attribution, retention, LTV, ROAS, and payback. Build datasets, pipelines, dashboards, cohort analyses, and predictive models; reconcile MMP, ad network, and internal data; investigate anomalies and fraud; analyze funnels; design incrementality and A/B tests; and recommend budget allocation and channel strategies to the UA team.

Conduct end-to-end analysis of complex healthcare data, including medical and pharmacy claims. Build and maintain SQL queries and analytical datasets, create visualizations, document methodologies, validate data, and translate findings into actionable business recommendations. Collaborate with analysts, data scientists, underwriters, product teams, account management, and cost-containment stakeholders to operationalize sustainable analytics solutions.

Leads analytics strategy for Zip’s emerging financial products, from market sizing and launch readiness through adoption, retention, risk, and unit economics. Partners with Product, Finance, Risk, and Operations leaders to define metrics, build scalable dbt models and reporting frameworks, analyze customer and portfolio behavior, and guide strategic decisions. Establishes SQL and analytics standards, mentors analysts, and translates complex findings into recommendations for executives.

Analyze and model marketing, product, and loan application data to optimize the borrower funnel and drive growth. Build BigQuery datasets, dbt models, and Tableau dashboards; evaluate customer behavior, acquisition costs, approval rates, and origination performance. Partner with Product, Marketing, and Engineering on A/B tests, statistical analysis, and actionable insights for leaders. Apply lending and fintech knowledge to improve conversion, customer value, and portfolio outcomes.

Lead data strategy and execution for emerging sectors, transforming large consumer datasets into accurate, scalable client insights. Responsibilities include resolving data-quality issues, designing workflows, maintaining sector taxonomies, partnering with product, revenue, engineering, and insights teams, and coaching analysts. The role requires hands-on analysis, production-grade data workflow development, stakeholder communication, and ownership of quality standards and methodologies in a rapidly evolving environment.

Analyze healthcare billing, payment, and medical review datasets; develop monitoring summaries and statistical analyses; support federal healthcare policy research; and collaborate with analysts and policy experts on project-based analytical solutions.

Analyze healthcare billing, payment, medical review, and policy datasets supporting federal healthcare programs. Responsibilities include integrating claims and operational data, producing monitoring summaries, evaluating medical review activities, querying data, researching healthcare payment policies, and collaborating with analysts and policy experts.

Analyze product, program, member, client, and operational data using advanced SQL in Databricks. Define KPIs and measurement frameworks, conduct segmentation and root-cause analysis, validate datasets, develop reporting, and translate findings into actionable recommendations. Partner with Product, Engineering, Operations, Client Success, and business leaders to improve performance and support strategic decisions.

Analyze cloud-platform data to support business decisions, define and maintain trusted metrics, and create reusable queries, dashboards, and documentation. Serve as the data-platform subject matter expert, support self-service analytics, validate data quality, identify anomalies, and partner with data engineering on source-level issues. Translate consumer needs into platform feedback and use AI tools to improve analysis, SQL drafting, documentation, and delivery speed.

Senior Data Analyst responsible for integrating sales, CRM, customer, campaign, product usage, and engagement data into forecasts, dashboards, recurring reports, datasets, and actionable insights. The role analyzes pipeline performance, customer health, product adoption, retention, churn, marketing campaigns, and commercial trends. It partners with cross-functional stakeholders, defines KPIs, improves data quality, prepares executive reporting, and supports strategic decision-making through clear analysis and recommendations.

Own end-to-end financial data analysis, including SQL and dbt data modeling, Looker dashboard development, data quality validation, reconciliation, and stakeholder-facing insights. Partner with Finance and Payments to support reporting, planning, revenue analysis, cost insights, and transaction-level analytics. Translate ambiguous business needs into reliable technical solutions while improving documentation, QA, modeling, and data architecture practices.

Own end-to-end product and marketing analytics for subscription products and web funnels. Define KPIs, build trusted dashboards and reusable SQL data models, analyze funnels, cohorts, retention, LTV, churn, and user behavior, and identify optimization opportunities. Maintain event tracking and taxonomy, monitor anomalies, communicate insights to stakeholders, and mentor junior and mid-level analysts. Collaborate cross-functionally with Product, Marketing, Data Engineering, and BI teams to support experimentation and data-driven decisions.

Own and scale end-to-end financial reconciliations across banking partners and internal systems. Develop data transformations, matching rules, monitoring, and reporting; investigate exceptions and resolve root causes with cross-functional teams. Define reconciliation requirements, support accounting close and audits, lead control initiatives, and mentor analysts. The role requires advanced SQL, transactional data expertise, knowledge of payment rails, reconciliation tools, BI dashboards, and experience in fintech or financial services.

Analyze product and business data to guide product strategy, growth, customer experience, and experimentation. Responsibilities include funnel, cohort, retention, segmentation, monetization, dashboard, and reporting analysis; defining metrics; maintaining event tracking; troubleshooting data quality; integrating data from analytics, advertising, payment, and CRM systems; and documenting tracking plans and metric definitions.

Analyze product telemetry, user signals, performance, behavior, feature adoption, and product metrics. Develop recurring reports, dashboards, and visualizations, investigate issues and trends, and provide insights supporting product initiatives and rapid iteration. Collaborate with Product Managers, Applied Scientists, Engineers, and stakeholders across China and the United States.

Conduct product analytics for MoneyGram’s digital money transfer products. Analyze customer behavior, product performance, experiments, feature releases, and cohort metrics to guide product strategy and growth. Build insights and reporting, collaborate with Product, Engineering, Marketing, Finance, and international teams, and improve analytics platforms, automation, and visualization processes. Translate complex findings into actionable recommendations for technical and non-technical stakeholders.

Supports insurance financial data analysis, source-to-target reconciliation, data conversions, reference data maintenance, and financial close activities. Validates premium calculations, investigates variances, supports General Ledger reporting, and documents audit and SOX evidence. Owns business and technical stories, manages development backlogs, coordinates testing and releases, and partners with finance, developers, QA teams, project managers, and senior leaders to deliver data and systems enhancements.

Supports value-based healthcare programs through complex SQL analysis, reporting, data reconciliation, program evaluation, payment support, and ad hoc analytics. Works with healthcare and insurance data, develops monthly reports, evaluates new opportunities, and communicates findings to senior and executive leadership. The role requires advanced Excel and large-scale data experience, with preferred expertise in Azure Synapse Analytics, Databricks, PySpark, or Python.