Top Remote Data Analyst Jobs

Review cyber-breach documents for accuracy and compliance, support data analysts to ensure data integrity, translate client requests into team directives, coordinate project timelines and resources, identify process issues, and contribute to continuous improvement initiatives.

Review cyber breach documents for accuracy and compliance, support data analysts to ensure data integrity, translate client requests into actionable directives, coordinate project timelines and resources, identify process issues, and contribute to continuous improvement to enhance workflow efficiency and quality.

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.

Drive Data Governance requirements, analyze and validate data, collaborate with stakeholders, and maintain Data Governance artifacts using SQL and Informatica tools.

The Data Systems Analyst oversees data onboarding into the cloud platform, monitors data quality, communicates needs, and leads training on data specifications.

The Senior Data Analyst transforms data into insights to guide business decisions, conducts analyses, and improves data collection systems.

Lead data management and quality efforts, consult with stakeholders and vendors, design processes and solutions, perform root-cause analysis of complex data errors, implement improvements, integrate technologies, validate deliverables, and present recommendations to senior management to enable AI-ready data and BI solutions.

Partner with business and product stakeholders to design, analyze, and interpret A/B tests and causal analyses, build Tableau dashboards and reports, present findings to non-technical audiences, and translate insights into actionable business recommendations.

Lead end-to-end evaluation, scoping, and onboarding of new healthcare data sources. Define field mappings, acceptance criteria, ingestion and entity-resolution rules, perform QA and anomaly detection, translate client requirements into integration specs, and produce maintainable documentation before handing off to maintenance teams.

Build and maintain scalable monitoring solutions and dashboards to track production, campaign, and operational data. Analyze large-scale datasets to detect anomalies, perform root-cause investigations with Engineering and Production Operations, and deliver actionable insights to improve platform reliability and operational efficiency.

Lead cross-functional analyses and build scalable reporting for go-to-market teams. Develop and automate data pipelines, create interactive dashboards, improve data quality, and translate complex findings into actionable recommendations for stakeholders and executives.

Lead marketing and digital analytics for financial institutions: analyze large datasets, build attribution and customer journey models, optimize campaigns via A/B testing, create executive dashboards and automated reports, and partner cross-functionally to improve customer experiences and marketing ROI.

Process, validate and QA large survey datasets; produce datasets, tables, codeframes and documentation; support weighting, testing and statistical analyses; learn and apply Python/R, automation and AI-assisted tools; improve automated processing workflows under senior guidance.

Senior data processing analyst responsible for end-to-end survey data processing: specifications, weighting, QA, documentation and deliverables. Produce datasets and tables, perform statistical tests, and modernise/automate workflows (Python/R, replace SPSS). Apply AI-assisted tools, act as technical lead for projects, and mentor junior analysts.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

Lead processing of survey data into cloud analysis tools, build dashboards and visualizations, train and support clients, collaborate across teams, and deliver high-quality work to meet project objectives and deadlines.

Senior Business Analyst specializing in advanced data visualization: create dashboards, choose optimal chart types for varied audiences, visualize high-dimensional data, apply statistics and financial modeling, collaborate with UX, and help drive execution.

Perform data cleansing, ETL, and preprocessing; analyze Retail CPG sales, inventory, and customer data; build predictive models for forecasting and segmentation; research and deploy Agentic frameworks and intelligent agents; produce visualizations and communicate insights to cross-functional stakeholders to optimize supply chain, marketing, and customer experience.

Analyze and consolidate disparate data sources, document functional specifications, review logical and conceptual data models, gather business requirements, validate implementations, support production deployments, investigate data quality issues, and coordinate with technology leads to resolve data completeness and accuracy gaps.

Lead reconciliation data analysis for cash, stock and position records. Gather requirements, document functional specs, validate solutions, support production deployments, investigate data quality and work with technology leads to ensure data completeness and lineage.

Design, build, and maintain interactive dashboards and visual products that translate complex operational and cybersecurity data into clear insights. Collect requirements, create mockups, automate analytics, and produce metrics for patching, vulnerability, and compliance to support executive and operational decision-making.

Analyze C&DS project data to produce actionable insights. Build data pipelines, reports, visualizations and predictive/prescriptive models. Collaborate with IT, data governance, and business stakeholders to enable data-driven decision-making, support reporting needs, and ensure data quality and access.

Own and QA high-impact retail data products: design and run QA, investigate and resolve complex data quality issues, collaborate with Insights and Engineering, improve automation and product reliability, and communicate methodology and limitations to clients.

The Data Insight Analyst develops reports and analyses using SQL and Excel, provides consultative insights into data trends, manages client requests, and configures mapping tools for data reporting and quality assurance.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.