Top Remote Data & Analytics Jobs in Boston, MA

The Senior Actuarial Support Analyst will analyze healthcare data, produce client-facing reports, and present insights to stakeholders. The role involves collaboration with various teams to improve customer value and reporting accuracy.

Lead analytics implementations using Google Analytics and Tag Manager for clients, providing mentorship and managing projects with a focus on enhancing clients' digital strategies.

This role oversees a team that analyzes MetLife's mortgage portfolios, delivers high-impact analytics, and collaborates with various stakeholders for reporting and compliance.

Support merchant onboarding, fraud detection, and risk analysis through data analysis and modeling. Collaborate cross-functionally to develop scalable monitoring frameworks.

The Financial Systems Analyst manages NetSuite, optimizes business system performance, supports users, ensures data integrity, and collaborates on process improvements.

Lead analytics strategy for a financial institution, ensuring compliance and driving marketing analytics through predictive modeling and team management.

The Senior Data Analyst will analyze data, build models, and provide insights to support decision-making for operational and leadership teams, while collaborating with technical and non-technical stakeholders.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Lead data governance for assigned domains: implement policies, monitor and remediate data quality, perform profiling and lineage documentation, track data quality KPIs, partner with stakeholders to embed standards, and support MDM and governance training.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.