Top Remote Data & Analytics Jobs

Support and develop BI applications for a client financial platform across environments. Build reports, analytics, and budgeting solutions (TM1), develop/tune Oracle SQL/PLSQL, deploy BI tooling, support UIs (low-code), follow Agile practices, and collaborate on integrations, security hardening, and operations.

Gather and verify metals recycling pricing data, set price assessments per methodology and IOSCO principles, write market commentary and news, expand and manage industry contacts, peer-review pricing, provide coverage for colleagues, engage markets through events and presentations, and handle market inquiries.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

Lead cross-functional analytics to inform clinical and operational decisions: build Tableau dashboards, create dbt analytical models, analyze large healthcare datasets (claims, EHR, HIE) with SQL, respond to ad-hoc requests via JIRA, and collaborate with product and engineering to improve data capabilities.

Founding data engineer to design and build Payabli's data platform: architect lakehouse/warehouse, build batch and streaming pipelines, model canonical datasets, ensure data quality/observability, enforce access/masking/lineage for regulated financial data, and enable analytics/ML feature pipelines while establishing team standards and CI/CD.

The IT Audit Senior Manager leads data-related audits, guides teams on corrective actions, analyzes audit results, and develops audit reports while addressing complex problems and mentoring colleagues.

The Quantitative Researcher will manage yield opportunities, design algorithms, perform risk analysis, and collaborate with engineers on DeFi strategies.

Lead and grow SQUIRE's Data organization as a player-coach, owning long-term data architecture, building reliable Snowflake pipelines, setting standards for modeling and data quality, hiring and budgeting for a 5+ person team, partnering cross-functionally, auditing integrations, and enabling AI/LLM use cases while remaining hands-on for high-risk technical work.

Build and maintain API-based data pipelines, analyze supply chain metrics, create dashboards and alerts, perform root-cause analysis, define KPIs with stakeholders, and document data models and integrations to improve logistics performance.

Lead the Decision Science function, designing ML models, overseeing experimentation frameworks, and ensuring model adoption across the company, driving operational and commercial improvements.