Top Remote Senior Data Analyst Jobs

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.

Lead marketing analytics across channel, campaign, cohort, and funnel performance. Build dashboards, reporting, AI-enabled analytical workflows, and data models that support marketing decisions. Conduct ad hoc analyses, evaluate attribution and incrementality, monitor data quality, and translate complex findings into executive recommendations. Partner with marketing and marketing science teams, influence strategic decisions, establish analytical standards, and mentor analysts.

Supports media reporting and measurement initiatives across client accounts by analyzing digital and traditional marketing performance data, developing KPI-aligned reporting, translating findings into optimization recommendations, and contributing to measurement frameworks. Partners with strategy, media, client services, data engineering, and data science teams to ensure data integrity and actionable outputs. Builds Tableau dashboards, supports reporting automation, interprets advanced analytics such as attribution and marketing mix modeling, and manages recurring and ad hoc deliverables.

Leads Gartner thought leadership and research on data management platforms, integration, architecture, operations, metadata, and AI-ready data. Develops market insights, forecasts trends, advises executive clients, supports sales, presents at conferences, reviews content, improves research processes, and mentors analysts. Requires deep data management expertise, strong research, writing, communication, analytical, presentation, and executive engagement skills, plus 15+ years of relevant experience and travel up to 25%.

The Senior Data Analyst gathers BI requirements, analyzes enterprise and offline datasets, writes and optimizes SQL queries, and builds dashboards using Power BI, Tableau, and Domo. The role translates business needs into technical specifications, designs dashboard wireframes, validates data, documents processes, and collaborates with engineering, product, and business teams. Knowledge of the US trust business is essential for interpreting data within financial and regulatory contexts.

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

Conduct forensic analytics for anti-money laundering and financial crime monitoring. Analyze large transactional datasets with SQL and Alteryx, identify suspicious behaviors and emerging typologies, develop and validate detection scenarios, calibrate thresholds, perform lookbacks and segmentation studies, evaluate transaction networks, and support AML investigations, SAR narratives, and regulatory responses.

Leads compensation analysis, market pricing, pay governance, annual compensation cycles, compliance audits, and data integrity between PayFactors and Workday. Provides executive-ready insights, develops compensation recommendations, manages cross-functional projects, maintains SOPs, supports survey submissions, and improves reporting and compensation processes. Partners with HR, Legal, and stakeholders to ensure competitive, equitable, compliant, and scalable compensation programs.

Owns advanced mobile and web analytics for the NPR App, including complex SQL analysis of raw BigQuery, GA4, and Firebase data. Leads A/B and multivariate experimentation, translates behavioral insights into product strategy, develops reporting and self-service tools, ensures data quality, and mentors colleagues and stakeholders on SQL, analytics, experimentation, and data governance.

Own product analytics for CookUnity’s marketplace, analyzing discovery, conversion, ordering, retention, customer behavior, and marketplace economics. Design and interpret experiments, define metrics and guardrails, build dashboards, validate instrumentation, and translate ambiguous product questions into actionable recommendations. Partner closely with Product, Design, Engineering, User Research, and business teams to guide decisions and improve customer experience, repeat ordering, and sustainable marketplace performance.

Leads requirements gathering, future-state process design, and scope definition for global product master data workstreams. Improves process efficiency, data quality, governance, and scalability through cross-functional stakeholder collaboration. Supports workflow definition, user stories, acceptance criteria, backlog readiness, prioritization, rollout activities, change management, and delivery handoffs. Uses SQL and enterprise data integration knowledge to validate and analyze structured data while supporting ERP-related processes and regional expansion.

Provides advanced decision science and analytics support across life, health, and annuity insurance. Gathers, transforms, and analyzes disparate data using statistical and quantitative methods; develops insight-to-action recommendations, visualizations, and executive presentations; documents methodologies and validation; and partners with product, underwriting, sales, and leadership teams to influence strategy and business outcomes.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.

Analyzes, cleanses, validates, and prepares operational datasets for mailing, email, reporting, billing, and processing activities. Develops Databricks queries and Alteryx workflows to automate processes and improve data quality. Performs audits, reconciliations, root-cause analysis, and corrective actions while maintaining governance and security compliance. Provides actionable insights, mentors junior analysts, communicates findings, and leads continuous improvement initiatives.

Own Kepler’s transaction data feed end-to-end, ensuring accuracy, improving methodologies, developing QA frameworks, solving complex analytical problems, and prototyping enhancements. Analyze massive datasets, automate workflows with AI, evaluate client-facing AI outputs, address high-complexity customer questions, and collaborate with Research, Product, Data Science, and Engineering teams.

Analyze platform, product, customer, advertising, and operational data to generate actionable insights. Build dashboards, reporting frameworks, automated workflows, and scalable analytics pipelines. Evaluate experiments and analytical methodologies, improve forecasting and data accuracy, and partner with product, engineering, marketing, revenue, and leadership teams to influence strategy, customer experience, and platform growth.

Analyze healthcare, financial, and utilization data to identify inefficiencies, support data-driven decisions, maintain dashboards, build analytical models, communicate insights, and monitor improvement initiatives across the organization.

Delivers recurring weekly and monthly sales reporting for Individual Life Insurance distribution partners. Maintains Tableau dashboards and reporting templates, validates and reconciles data across sources, investigates discrepancies, handles routine ad hoc requests, follows documented processes, and escalates complex issues. The role requires accurate execution, clear communication, sound judgment, and continuous improvement of reporting quality and efficiency.

Conducts data collection, cleaning, management, statistical and computational analysis for education policy research. Responsibilities include building reproducible ETL pipelines, creating visualizations and research materials, applying machine learning and natural language processing, validating model outputs, managing restricted-use data, reviewing analyses, and coordinating with external collaborators. Senior responsibilities include overseeing analytical projects, documenting methodologies, managing compute and API costs, and serving as a technical contact.

Design and administer enterprise dashboards and reporting solutions (Tableau, Power BI, Microsoft Fabric). Translate complex business questions into compelling data stories, partner with stakeholders and BI engineers, champion visualization standards and governance, mentor analysts, and improve reporting usability and trust across the organization.

Transform HR data from HRIS, payroll, timekeeping, and workforce systems into dashboards, reports, visualizations, and actionable insights. Analyze workforce trends involving headcount, turnover, hiring, attendance, and retention. Partner with HR, business, and IT teams on workforce planning, data quality, system integrations, HR technology, and strategic initiatives while ensuring data accuracy, privacy, and compliance.

Owns enterprise data governance activities, including metadata management, data cataloging, data quality rules, lineage, profiling, report certification, PII handling, and governance workflow automation. Partners with data stewards, IT teams, business stakeholders, and senior leaders to improve data integrity, regulatory compliance, reporting quality, and governance processes. The role also supports training, stakeholder workshops, process improvement, and mentoring of less experienced professionals.

Lead paid media analytics for Life Company, using SQL/Python and advanced statistics to measure and optimize paid social/search and AI-powered search. Build audience segmentation, run incrementality/experimentation, create visualizations and recommendations, and partner with marketing to drive acquisition and engagement.

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.

Own high-impact data products, ingestion pipelines, and granular data feeds end to end. Analyze massive datasets to answer client and stakeholder questions, ensure data accuracy, and derive actionable insights. Improve products and pipelines by developing methodologies, scaling third-party datasets, and creating data modules. The role requires clear communication, attention to detail, methodical problem solving, prioritization, experimentation, and strong ownership. Training includes SQL, PySpark, Python fundamentals, and internal tools.