Top Remote Data & Analytics Jobs in Philadelphia, PA

Lead cross-functional analyses and build scalable reporting for go-to-market teams. Develop and automate data pipelines, create interactive dashboards, improve data quality, and translate complex findings into actionable recommendations for stakeholders and executives.

Design and operationalize FHIR-compliant data models and scalable integration solutions to harmonize EHR, HIE, and claims data. Build validation frameworks and automated rules to ensure clinical accuracy and longitudinal integrity. Produce clear documentation and collaborate with engineering and cross-functional teams to support analytics, operational, and research initiatives.

Lead architecture and delivery of enterprise data transformation on the Guidewire Data Platform. Drive design, ingestion/egress, migration performance, and AI-enabled tooling. Facilitate inception and design review sessions, mentor teams, coordinate with partners, and ensure successful data platform adoption and repeatable delivery practices while spending significant time on customer sites.

As a Data Engineer, you will design and maintain data pipelines, support DoD systems, and ensure data quality and compliance.

Own RevOps data models and BI infrastructure to drive GTM strategy. Clean and analyze datasets, build predictive models, define and track leading/lagging KPIs, deploy dashboards, document data definitions, and deliver executive-ready insights while partnering cross-functionally with Finance and GTM teams.

Lead and grow an analytics engineering team to build a trusted semantic metrics layer, scalable dimensional models, and governance. Partner cross-functionally to deliver reliable data products, improve pipelines and observability, set technical standards, and enable self-service analytics, experimentation, and ML while balancing scalability and business impact.

Perform default reporting and analytics for mortgage servicing portfolios, validate and troubleshoot data and exception reports, conduct root-cause analysis, produce ad-hoc reports, document processes, and collaborate with default management to ensure regulatory-compliant, accurate reporting delivery.

Process, validate and QA large survey datasets; produce datasets, tables, codeframes and documentation; support weighting, testing and statistical analyses; learn and apply Python/R, automation and AI-assisted tools; improve automated processing workflows under senior guidance.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Own and build customer health, usage/adoption, and product configuration data models. Produce ad-hoc and recurring analyses to identify upsell/expansion opportunities, partner with CS, Sales, Product, and Data teams, and present actionable insights to leadership to drive revenue-relevant actions.