Top Remote Data & Analytics Jobs in Philadelphia, PA

Lead end-to-end product analytics: instrumentation, data quality, funnels, retention, and experimentation. Use SQL and Python for analysis, build dashboards, partner with product and growth, and improve analytics infrastructure (Amplitude and data warehouse migration). Remote with GMT+1 overlap.

Lead analytics to improve player experience, engagement, retention, and monetization. Analyze player lifecycle, run cohort and funnel analyses, design and evaluate A/B tests, build dashboards, define product metrics, investigate KPI changes, and partner with product, marketing, engineering, and data teams to deliver data-driven recommendations and improve data quality.

Manage CVS Health's data partnerships and monetization strategy, source new partnerships, ensure operational success, and drive data product adoption across analytics teams.

The VP of Data will oversee 9amHealth's data functions including data engineering, analytics, and data science while collaborating with executive teams to shape data-driven strategies and improve member experiences in chronic condition management.

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.

The Data Engineer will build and maintain data platforms, deploy pipelines, monitor transformations, and collaborate with Data Scientists and DevOps.

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

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

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.

Drive Data Governance requirements, analyze and validate data, collaborate with stakeholders, and maintain Data Governance artifacts using SQL and Informatica tools.