Top Remote Blockchain Data & Analytics Jobs

Own fraud detection and mitigation for ACH payments: design controls, run investigations, analyze performance (precision/recall, financial impact), and partner with Product, Data Science, Risk ML, and Engineering to operationalize risk strategies and transition to model-driven controls.

The Staff Data Analyst will lead data strategy for Compliance, analyzing regulatory engagements, and driving effectiveness through actionable insights and collaboration across various teams.

Lead design and optimization of data models and pipelines for compliance and risk; standardize metrics and documentation; build data quality, lineage, and monitoring (including AI agents for automation); manage ETL scheduling, on-call pipeline support, and collaborate with product and non-technical partners to translate business needs into automated, production-ready data solutions.

The Senior Analyst leads enhancements of the Internal Audit OpenPages, ensuring successful deployment, training, and adoption of data-driven solutions, while collaborating with teams across the organization.

The role involves improving transaction monitoring rules, analyzing risk patterns, and building dashboards for compliance while collaborating with investigations and compliance leadership.

The role involves analyzing market data to identify trading opportunities, designing strategies, and implementing trading systems for a quantitative finance team.

Participate in a fixed-term accelerator program conducting data automation and aggregation to build dashboards, perform quantitative analysis to identify risk events and loss exposure, and investigate cases to categorize risk typologies and summarize behavioral patterns.

Lead retention and marketing analytics: build lifecycle and segmentation frameworks, design and analyze A/B tests, drive personalization and KPI dashboards, automate retention reporting, and partner with Marketing, CRM, Product, and Data Engineering to turn insights into action.

Analyze blockchain data, creating efficient query solutions and fraud detection methodologies while ensuring data integrity and transforming customer data needs into actionable insights.

Design and implement scalable dimensional data models, data transformation pipelines, and BI solutions. Partner with product, engineering, and business stakeholders to translate requirements into trusted datasets, perform analysis and root-cause investigations, build automated data quality and validation frameworks, optimize SQL and transformations, and document data assets and processes.