Top Remote Analysis Reporting Jobs in Boston, MA

The Workday Reporting & Data Analyst will design and optimize reporting solutions, enhance data accuracy, and deliver insights through Workday and Power BI while collaborating with HR leaders.

The Senior Pricing and Paywalls Product Analyst will automate analytical data collection, analyze product metrics, organize A/B tests, and support the generation of product hypotheses to identify growth opportunities.

Lead clinical performance and outcomes reporting across facilities; analyze and distribute clinical data to support quality improvement, decision making, and resource utilization. Provide analytic leadership, train users, liaise with vendors, develop reporting processes, and support facility and enterprise quality and safety goals.

Analyze and forecast financial, economic, and market data to support strategic and operational decisions. Develop premium variance reports, set monthly revenue targets, perform A:E analyses, expand explanatory driver interfaces, ensure data integrity and controls, troubleshoot anomalies, and collaborate with actuarial and finance partners.

Build and maintain a near real-time financial dashboard by integrating market and forecast APIs, automating financial models, and crafting clear visual narratives using Flourish and Canva. Collaborate with design and marketing partners, ensure data accuracy and performance, and optimize data flows across multiple feeds.

The Manager of Solutions Engineering will lead a team of Solutions Engineers, focusing on customer engagement, technical demonstrations, and mentoring while enhancing POC success.

The Data Analyst will support operational reporting and stakeholder needs, working with SQL and Artiva to meet business requirements through data and reporting solutions.

Lead planning, oversight, and coordination of Athlete Intelligence and Data projects, manage cross-domain alignment and stakeholder engagement, and facilitate program delivery and reporting in a complex environment.

Build and own the reporting and insight layer: write optimized Redshift queries, build dashboards, monitor model feedback signals, triage and prioritize investigations for data science, maintain ETL pipelines ingesting semi-structured data, and enable Customer Success with clear metrics and onboarding checks. Move into model validation and automation to scale analytic workflows.

Own support analytics for User Operations: build dashboards and recurring reports, track north-star metrics (cSAT, TTR, QA, escalations), instrument Zendesk, connect support to product/customer data, quantify operational costs of bugs, and measure AI-driven support performance.