Top Remote Data Analyst Jobs

Collect, process, and analyze large datasets using statistical methods to answer business and risk-management questions. Develop dashboards, narratives, KPIs, data processes, and analytics capabilities; maintain data quality; query databases; resolve data issues; translate business problems into functional and technical requirements; and manage key tasks, resources, schedules, and costs.

Analyzes and interprets data, evaluates results, and provides actionable insights to support strategic decision-making across departments.

Analyze banking and financial crime data, develop and tune statistical and machine learning classification models, evaluate model performance, identify data quality issues, and recommend optimization strategies. The role uses Python and SQL for feature engineering, statistical modeling, automation, and large-scale data processing. Responsibilities also include documenting methodologies, reporting results to management and regulators, and collaborating with compliance, technology, business, and model governance teams.

Develops and improves clinical site payment forecasting models, integrating enrollment, operational, and Medidata Payments data. Produces client-ready financial forecasts and reports, analyzes budget utilization and forecast variances, supports revenue recognition, audit compliance, and final payment reconciliations, and collaborates with Clinical Operations, Revenue Recognition, Project Analysis, and Clinical Payments teams across the study lifecycle.

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.

Owns end-to-end customer analytics workstreams, including KPI frameworks, multi-source dashboards, reporting, data governance, quality assurance, and insight delivery for government digital communications programs. Presents recommendations to stakeholders, mentors junior analysts, leads Agile ceremonies, documents analytics practices, resolves data issues, and evaluates AI-assisted analytics tools.

Develop and automate supply chain and logistics reports and dashboards, analyze large datasets, monitor operational KPIs, ensure data accuracy, and identify process-improvement opportunities. The role supports inventory, transportation, warehouse operations, and demand planning while collaborating with operations, procurement, finance, and IT teams. It also involves root-cause analysis, process documentation, and continuous improvement initiatives.

Analyzes complex datasets using advanced statistical methods, experiments, predictive models, forecasting, segmentation, and regression. Develops measurement frameworks, KPIs, and reproducible workflows; integrates and validates large datasets; and translates findings into actionable recommendations for clients and internal teams. The role partners on optimization and go-to-market strategies, communicates insights to technical and non-technical audiences, and supports client meetings and occasional field ride-alongs.

Analyzes complex datasets and applies advanced statistical methods to evaluate marketing programs, customer behavior, sales performance, and promotional effectiveness. Develops KPIs, measurement frameworks, experiments, predictive models, and reproducible workflows. Translates findings into actionable recommendations for clients and internal stakeholders, supports data-driven go-to-market strategies, and communicates insights to technical and non-technical audiences using Python, R, SQL, and visualization tools.

Collects, cleans, validates, and analyzes data from multiple sources. Develops dashboards, reports, and visualizations using SQL, Excel, Power BI, or Tableau. Identifies trends, monitors data quality, supports KPI tracking, and delivers actionable insights for business decisions. Collaborates with stakeholders, documents analytical processes, prepares regular and ad hoc reports, and recommends process improvements based on data.

Develops and delivers ad hoc, recurring, and dashboard-based HR reports using data from systems such as Oracle HCM, Power BI, and Excel. The role extracts, cleans, validates, and analyzes workforce data; translates stakeholder needs into reporting requirements; ensures data privacy and integrity; documents processes; and identifies opportunities for automation and process improvement. It also supports HR users and collaborates with business and leadership teams.

Develops HR reports and dashboards, fulfills urgent data requests, extracts and validates data from multiple systems, and translates stakeholder needs into reporting requirements. Ensures data integrity, privacy, and compliance while documenting processes and identifying automation opportunities. Collaborates with HR, Finance, leadership, and business teams, supports reporting-tool proficiency, and may provide technical guidance and training.

The Finance Data Analyst manages finance ETL processes, reconciles enterprise data warehouse outputs, investigates discrepancies, and validates insurance financial data. Responsibilities include SQL-based analysis of premiums, commissions, taxes, fees, and payments; building automated controls and exception reports; supporting Finance reporting and close activities; documenting data processes; and partnering with Finance and data engineering teams to improve data quality and reliability.

Analyze B2B commercial data to identify growth opportunities, design experiments, evaluate pricing and credit-limit initiatives, and measure business impact. Apply SQL, Python, statistical analysis, A/B testing, difference-in-differences, causal inference, and forecasting methods. Work independently with commercial and project teams to support pricing, market expansion, and partner analytics decisions.

Develops dashboards, data models, reports, and analytical solutions that transform raw data into actionable business insights. Partners with stakeholders, provides technical guidance, documents architectures and processes, troubleshoots analytics solutions, and communicates findings to technical and non-technical audiences. Requires advanced Spotfire, SQL, business intelligence, and data analytics expertise, with knowledge of Databricks, Power BI, Python, R, Salesforce, and modern data architecture.

Analyzes electric vehicle charging station and session data from multiple network providers. Responsibilities include building automated data-transfer frameworks, quality-controlling and cleansing datasets, managing database ingestion, producing utilization reports and visualizations, and deploying code to cloud platforms. The role supports clean-energy and transportation-electrification initiatives and requires collaboration, organization, advanced Excel skills, and data analysis experience.

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Supports Epic and other healthcare information systems through application configuration, database queries, reporting, testing, workflow design, troubleshooting, training, security, and post-launch support. Acts as a liaison among end users, clinical and business leaders, vendors, and technical teams. Develops data-driven solutions, documents system changes, coordinates service requests, and provides 24/7 on-call support for critical applications.

Analyzes Recidiviz interventions using Python and SQL, builds statistical models, measures historical and projected impact, develops automated metrics workflows, and communicates findings to stakeholders. The role defines product usage and impact measures, supports experimental and quasi-experimental analyses, and informs product strategy and fundraising partnerships focused on criminal justice outcomes.

Serve as a strategic analytics partner across Product, Growth, Engineering, Design, and Leadership. Define KPIs, measurement frameworks, experimentation strategies, and A/B tests; build executive dashboards and scalable dbt datasets; deliver product and marketplace insights; manage technology-category and vendor data; research cybersecurity and AI markets; and use LLMs to improve workflows and enrich the product database.

Analyze customer lifecycle and Customer Success data to measure attribution, campaign performance, product adoption, retention, and revenue impact. Build multi-touch attribution models, integrate digital engagement data with Gainsight and CRM events, clean and unify datasets, segment audiences, identify journey bottlenecks, and create Tableau or Looker dashboards. Partner with Campaign Strategy, Product Insights, and CS Operations teams to deliver actionable recommendations and improve automated and human customer interventions.

The Data Analyst develops and maintains Power BI dashboards, datasets, data models, SQL and DAX solutions, and data pipelines. The role supports AWS cloud analytics integration, data quality, troubleshooting, governance, documentation, and workspace administration. It coordinates data engineers, translates business requirements into technical deliverables, collaborates with stakeholders, and communicates findings to nontechnical audiences while supporting agile delivery and data privacy compliance.

Supports data analysis, cleaning, mining, dashboarding, SEO research, marketing analytics, and AI or chatbot workflows. Collaborates with educators and technical teams to validate analytics models, develop data infrastructure, identify student needs, and improve educational programs. Uses SQL, Python data tools, Excel, web analytics, and visualization platforms to generate actionable insights and document evolving workflows.

Owns fraud and market-abuse detection models, rules, and partner-facing surveillance reporting across trading data. Investigates wash trading, collusion, hedging, reverse trading, and other suspicious activity; calibrates thresholds, validates false positives, maintains data quality, and produces evidence-based findings. Requires strong SQL, cloud data warehouse experience, futures and derivatives knowledge, anomaly detection expertise, and the ability to communicate findings to partners and executives.

Maintains financial master data, approval mappings, chart of accounts, cost and profit centers, reporting structures, and related documentation. Manages user requests, SLAs, data analysis, controls, process improvements, training, and ERP implementation support. Collaborates with global stakeholders to ensure accurate, policy-compliant finance master data across business systems.