Top Remote Data Analyst Jobs

Develop resource allocation, demand forecasting, and capacity models for Customer Success. Analyze quantitative and qualitative data, identify trends and risks, and translate findings into actionable recommendations. Partner with finance, planning, delivery, and leadership stakeholders to refine assumptions, resolve complex business issues, and support regional implementation. Present insights to senior leaders and manage cross-functional priorities in an ambiguous, fast-paced environment.

Supports information collection and organization for manuals, training materials, installation guides, proposals, and reports. Edits technical and customer-facing documentation, assists with financial and administrative tasks, and maintains systems, operations, and procedural documentation libraries. Collaborates remotely with project managers, requirements analysts, Scrum Masters, developers, testers, and government stakeholders in Agile ceremonies while complying with CUI and cybersecurity requirements.

Build and maintain Engine X performance dashboards, reporting frameworks, data models, and complex SQL analyses using Snowflake. Track card, booking, rewards, spending, and retention metrics; investigate anomalies; support A/B tests; document metric definitions; and communicate findings to product, finance, and leadership. Collaborate with analytics and data engineering teams to validate pipelines and improve data quality.

Analyze telematics, IoT, sensor, and firmware data to evaluate hardware performance, reliability, and field issues. Build dashboards and reports, identify trends and anomalies, apply statistical and machine learning techniques, validate firmware improvements, and provide actionable insights to engineering, product, data science, and customer support teams. Help develop scalable data pipelines and promote data-driven hardware and software development.

Analyze clinical outcomes, engagement, feature usage, ROI, and business trends for client reporting. Build and maintain complex SQL queries, reporting workflows, interactive dashboards, and self-service analytics. Partner with Customer Success, Sales, Marketing, Finance, Product, and Medical Affairs to deliver actionable insights, executive presentations, and client-facing materials. Improve data quality, automate recurring reporting, and identify opportunities that support client outcomes and business growth.

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.

Develops forecasting, optimization, machine learning, and decision-support models for wholesale power markets. Analyzes load, prices, congestion, generation, transmission, fuel, settlements, and portfolio risk to improve market strategies and asset performance. Builds analytical datasets, data pipelines, dashboards, and business intelligence solutions with IT and business teams. Supports MISO bidding, resource adequacy, settlement validation, scenario analysis, and strategic planning while communicating recommendations to technical and executive stakeholders.

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.

Delivers technical customer implementations involving software installations, integrations, upgrades, application and database migrations, ETL, and data conversions. Develops and tests code modules, supports SQL Server and Windows/IIS environments, diagnoses technical issues, performs quality assurance, and applies AI-assisted automation. The role collaborates with customers and internal teams, documents solutions, supports project budgeting, and contributes to scalable service delivery components under established guidance.

Supports data security projects and daily information protection operations. Implements and manages DLP and data classification solutions, monitors data-sharing activity, investigates potential data loss, and maintains compliance documentation and reports. Troubleshoots security issues, supports sensitive information handling, and collaborates with IT and security teams to improve organizational security. The role requires knowledge of DLP, encryption, secure file transfers, cloud and network security, and applicable security standards.

Leads SAP MDG functional design and delivery across master data domains, including requirements, governance, workflows, testing, data migration readiness, stakeholder decisions, and continuous improvement. Guides technical teams on configuration, integrations, and development while owning functional specifications, acceptance criteria, solution decisions, and business sign-off. Requires strong SAP MDG experience, cross-functional leadership, and expertise in Material, Business Partner, and/or Finance master data.

Analyzes healthcare and business data from multiple sources to create reports, dashboards, forecasts, and actionable insights. Develops SQL- and Excel-based reporting solutions, validates data quality, supports claims and utilization analysis, fulfills regulatory reporting requirements, and improves reporting workflows. Collaborates with stakeholders to define requirements, presents findings, documents methodologies, and supports analytics projects, audits, and process automation.

Analyze credit and fraud risk across BNPL products, monitor portfolio performance and risk indicators, optimize approval and loss-reduction strategies, support risk model and policy launches, and present insights to leadership. Collaborate with data, product, finance, and commercial teams across multiple markets while improving risk operations and reporting automation.

Leads development and maintenance of actuarial data marts, datasets, extracts, reports, and analytical solutions supporting claims analysis, IBNR reserving, forecasting, trend analysis, and financial reporting. Partners with actuarial, finance, medical economics, and data teams to validate and reconcile healthcare data, automate refreshes, ensure auditability, and improve data quality. Provides technical leadership, requirements expertise, recommendations, training, and direction to junior staff and business partners.

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.

Lead finance data governance, quality validation, reconciliation, SOX control execution, audit support, and finance-system integration initiatives. Define data standards, lineage, controls, and validation criteria across ERP, subledger, reporting, and interface environments. Partner with Accounting, Finance, Technology, and business teams on requirements, testing, cutover, defect resolution, change management, and post-production validation to ensure accurate, complete, traceable, and reliable financial data.

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.

Analyzes complex healthcare and revenue cycle data to identify trends, measure operational and financial performance, and provide actionable recommendations. Develops reports, dashboards, analytical models, and structured datasets using SQL, Databricks, and BI tools. Partners with cross-functional teams to define requirements, validate data, communicate insights, and support continuous improvement initiatives.

Supports data stewardship and governance workflows, including metadata, taxonomies, data-use agreements, MOUs, ISAs, responsible data-use practices, and governance evidence. Provides Trustworthy AI governance support through model documentation, risk assessments, monitoring outputs, issue logs, and corrective-action tracking. Collaborates with technical, security, quality, governance, and customer-facing stakeholders while documenting decisions, risks, and delivery evidence.

Analyze and connect complex datasets to generate actionable business insights and improve data products. Gather and manage requirements, document processes, define acceptance criteria, support testing, and collaborate with engineering and data teams. Serve as a data subject matter expert while advancing data quality, stewardship, lineage, metadata management, and stakeholder alignment across digital, direct-to-consumer, sports, fan, and business use cases.

Collects, cleans, validates, and analyzes data from multiple sources. Builds reports, dashboards, and visualizations; writes SQL queries; documents data definitions; checks data quality; and presents findings to technical and non-technical stakeholders. Supports ad hoc data requests and helps client program leaders make informed decisions. The role is fully remote and requires strong communication, analytical, and independent-working skills.

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.

The Investment Technology Business Analyst will deliver front-office technology and data implementations for asset and wealth management clients. Responsibilities include business analysis, SQL-based data work, data modeling, governance and quality management, cloud data platform implementation, and expertise across investment processes such as risk, performance, compliance, reporting, derivatives, operations, or investment data. The role also involves leading small to medium-sized consulting teams, developing technical solutions, managing client relationships, and traveling as needed.

Lead analytics for subscription products and web funnels, partnering with Product, Marketing, and Data teams to improve conversion, retention, and LTV. Build trusted dashboards, SQL data models, event tracking structures, funnel and cohort analyses, and A/B testing insights. Monitor metrics, identify anomalies, communicate recommendations, and mentor junior and mid-level analysts while maintaining reliable reporting and data foundations.

Executes technical data governance, data quality, metadata management, and Collibra administration. Performs data profiling, implements quality rules, maintains metadata lineage and asset diagrams, reports on quality metrics, and supports incident root-cause analysis. Requires strong SQL, Collibra, and data quality tooling experience, with preferred API integration and cloud data environment experience.