Top Remote Senior Data Analyst Jobs

Senior Data Analyst responsible for building financial reporting data models, business logic, reporting layers, and automated solutions supporting regulatory compliance. Partners with product, engineering, accounting, treasury, and finance teams to investigate data issues, improve financial system transparency, resolve reporting problems, and communicate findings to technical and non-technical audiences.

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.

The Senior Data Analyst will develop and improve Sigma dashboards, reporting, and business intelligence capabilities. Responsibilities include gathering stakeholder requirements, querying and analyzing complex datasets with SQL, improving data quality and governance, defining metrics, automating reporting processes, and partnering on Snowflake data modeling and warehouse improvements. The role also evaluates analytics tools, delivers actionable insights, and communicates findings to technical and non-technical audiences.

Build the financial reporting function for a new iCasino division from scratch. Own data modeling, SQL and dbt transformations, dashboards, recurring reports, KPI tracking, and business insights using Snowflake, Sigma, and Oracle. Partner with engineering, finance, compliance, operations, and commercial teams; communicate findings to stakeholders; develop scalable BI solutions; leverage GenAI tools; and mentor others on analytics and BI best practices.

Analyzes and manages Medicare Advantage eligibility, utilization, and benefit data. The role validates data accuracy, supports vendor data exchanges, troubleshoots production issues, performs SQL-based ad hoc analysis, and ensures compliance with CMS and organizational standards. It collaborates with product owners, vendors, IT teams, and business stakeholders to design scalable data solutions, communicate findings, manage requirements, and drive projects to completion.

The Senior Data Analyst develops advanced SQL analyses, maintains Tableau and Hex dashboards, validates warehouse metrics, and translates data into actionable recommendations for executives, funders, government audiences, and community partners. The role emphasizes data storytelling, reporting standards, secure PII-aware delivery, stakeholder collaboration, and business impact evaluation. It also offers growth into AI-assisted analytics, custom visualization, and data-to-report automation.

Build network capacity and demand forecasts across 50 states, support clinician recruitment and retention analytics, measure clinical and scheduling outcomes, and design experiments with Product and Engineering. Develop governed data models, KPI definitions, and AI-powered analytics infrastructure. Serve as the primary analytics partner for Network leadership by translating complex, multi-source data into actionable recommendations and presenting insights to technical and executive audiences.

Analyze customer journeys, churn, acquisition, activation, retention, attribution, experimentation, and conversion. Develop advanced models and actionable strategy recommendations for B2C Marketing. Partner with stakeholders and data engineering to define metrics, improve data quality and governance, and build scalable dashboards using modern analytics and visualization tools. Independently manage multiple complex projects and identify opportunities that support business objectives.

Develop scalable analytics assets and serve as the Power BI/Microsoft Fabric expert. Build and publish trusted datasets, semantic models, and dashboards; author Databricks workflows and production SQL; apply R for statistical analysis; ensure governance, versioning, and reproducibility; partner with stakeholders and Data Engineering to deliver high-impact insights, define KPIs, and communicate executive-ready recommendations.

Develops scalable analytics products and workflows using Databricks, SQL, R, Power BI, and related tools. Partners with finance and revenue cycle stakeholders, builds KPIs and self-service reporting, analyzes complex datasets, validates results, and presents actionable recommendations to executives. The role requires production-level SQL, statistical and financial analysis, reproducible Git-based workflows, BI development, stakeholder leadership, and measurable business impact.

Analyze customer journeys, churn, acquisition, activation, retention, conversion, attribution, experimentation, and media mix performance. Build advanced analyses, models, metrics, and scalable dashboards that support B2C Marketing decisions. Partner with stakeholders and data engineering to improve data quality, governance, reporting adoption, and strategic outcomes while independently managing multiple complex projects.

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.

Partners with business leaders to analyze performance metrics, funding, compliance, enrollment, and retention data. Builds scalable analytical models, datasets, reports, dashboards, and forecasting tools using Python and SQL. Translates complex business rules into structured calculations, validates analytical outputs, identifies trends and risks, and delivers actionable insights supporting strategic, financial, and operational decisions.

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.

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.