Top Remote Senior Data Analyst Jobs

Maintains and enhances product configurators using product and pricing data. Responsibilities include launching and discontinuing products, updating distributor offerings and pricing, testing system releases, protecting data integrity, identifying cross-system risks, documenting standards, supporting AI-assisted validation, leading configuration initiatives, improving processes, and coaching team members.

Develop complex analytics, dashboards, data products, ETL/ELT pipelines, and reporting solutions supporting Medicare Advantage supplemental benefits. Analyze eligibility, utilization, and operational data; ensure data quality, compliance, and governance; translate findings into recommendations for leadership, vendors, and stakeholders; manage concurrent initiatives; improve processes; document solutions; and mentor team members.

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.

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.

Own experimentation analytics across Product and Marketing, including A/B and multivariate test design, causal inference, statistical analysis, dashboards, dbt models, and data infrastructure. Translate results into business recommendations, improve experimentation frameworks and self-service reporting, partner with engineering on instrumentation, mentor analysts, and manage the analytics roadmap.

The Senior Data Analyst will support Growth and Product teams through paid-channel analysis, user journey optimization, activation and retention insights, and churn reduction. Responsibilities include developing experiments, analyzing ad network performance, improving tracking and instrumentation, ensuring data quality, and enabling self-service analytics. The role requires translating complex data into actionable recommendations and communicating effectively across technical and non-technical teams in a fast-paced SaaS environment.

Analyze and maintain recruitment, onboarding, workforce, participant, and program-performance data for the NIH DataForce Service Program. Develop trackers, dashboards, reports, and briefing materials; monitor participant lifecycle activities; identify data-quality issues, risks, trends, and process improvements; and support recurring monthly and quarterly analyses. Collaborate with program managers, mentors, coordinators, and government stakeholders while protecting sensitive information and ensuring Section 508 accessibility compliance.

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.

Own product analytics and measurement strategy, including KPI definition, experimentation, reporting, executive dashboards, and scalable dbt datasets. Partner with Product, Growth, Engineering, Design, and leadership to guide roadmap and marketplace growth decisions. Conduct product and market analysis, manage technology-category data, research cybersecurity and AI markets, and use LLMs to improve workflows and enrich the product database.

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.

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.

Designs and delivers predictive, prescriptive, and diagnostic analyses that guide strategic decisions. Owns the analytical lifecycle, including hypothesis development, statistical and machine learning modeling, experimentation, metric governance, data quality, documentation, and executive insight delivery. Partners cross-functionally to define meaningful KPIs, validate analytical outputs, lead analytics projects, measure business impact, and strengthen organizational analytical capabilities through training and methodological guidance.

Analyzes and validates healthcare, operational, clinical, and financial data to support performance improvement. Develops dashboards, reports, visualizations, automated analytics, data models, and queries using Microsoft Fabric, Power BI, SQL, and Python. Works with Epic EHR and Clarity datasets, maintains reporting standards, and partners with clinical, operational, and financial leaders to deliver actionable insights.

Collect, process, and analyze large datasets using statistical methods to answer business questions. Develop dashboards, narratives, KPIs, and actionable insights; maintain data processes and analytics capabilities; ensure data quality; resolve data issues; and translate business problems into functional and technical requirements. Coordinate key tasks and resources to meet cost and schedule objectives while collaborating across departments.

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.