Top Data & Analytics Jobs in Providence, RI

Own and optimize data infrastructure and ETL/ELT pipelines using SSIS and Microsoft Fabric. Build and maintain SQL Server data warehouse staging, transformations, and lakehouse ingestion. Implement CI/CD, version control with GitHub, monitor pipeline health, troubleshoot data issues, document data flows, and translate stakeholder requirements into data engineering solutions that support BI reporting.

Lead development and governance of the supply chain data warehouse and analytics platforms. Build SQL-driven models, dashboards, and KPIs to drive inventory optimization, cost reduction, supplier performance, and working capital improvements. Support ERP integrations and data migrations, perform deep data discovery and predictive analytics, and present actionable insights to senior leaders to enable strategic decision-making.

The Product Analyst will design experiments, analyze user behavior, and communicate insights to drive engagement and retention decisions effectively.

Investigate and analyze suspected fraud cases, monitor and validate fraud strategies, develop countermeasures, evaluate risk scenarios, and collaborate cross-functionally to improve fraud detection and minimize false positives/negatives.

Lead revenue operations and business insights by owning GTM and revenue data integrity. Build reporting and AI-driven insights, run billable usage analysis, manage data flows with Fivetran/Salesforce/Sigma, investigate billing disputes, and translate data into actionable narratives for leadership.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

Lead development of credit and fraud strategies using data, ML models, and advanced analytics. Design A/B tests, analyze portfolio performance, conduct root-cause and ad-hoc analyses, and partner with Data Science, Product, and Engineering to implement and validate risk and fraud prevention strategies while communicating findings to stakeholders.

Lead technical data exchange and onboarding for client file feeds, own inbound data quality and acceptance criteria, detect and resolve quality degradation, document integrations and specs, coordinate with engineering/product/analytics and client teams, and drive standardization and process improvements to ensure timely, spec-compliant file exchanges and SLA adherence.

Lead design, build, and maintain scalable batch and streaming data pipelines and data warehouse models. Ensure data quality, observability, performance, and security. Own workstreams, support production incidents, and enable analysts and downstream applications.

The Director, Analytics Infrastructure & Pipeline Operations is responsible for creating automated data pipelines and centralized feature stores for data science, leveraging AI technologies to optimize workflows and ensure data quality.