Top Data & Analytics Jobs in Philadelphia, PA

Own supervisory data management and governance as a subject matter expert. Define data quality rules, metrics, monitoring, issue remediation, taxonomies, metadata, and cataloging practices. Partner with business, IT, and platform teams to improve data reliability, accessibility, lifecycle management, and future AI readiness. Translate business needs into technical requirements, facilitate adoption of governance practices, and communicate recommendations to technical and executive audiences.

Designs and develops scalable data architectures, pipelines, data warehouses, and analytics solutions across on-premise, cloud, and hybrid environments. Performs data wrangling and discovery, collaborates on business intelligence initiatives, mentors data engineers, contributes to technical capability development, and supports project planning and estimation.

Analyzes operational performance metrics, generates recurring and ad hoc reports, audits data integrity, identifies process issues, and recommends improvements. The role builds reporting tools, consolidates data, compares performance against budgets, evaluates strategic proposals, and provides analytical insights to support business decisions. It requires independent judgment, collaboration with management, and flexibility to work nights, weekends, and variable schedules.

Leads data strategy for MetLife’s Group Benefits business by connecting business and Data & Analytics teams, establishing shared definitions, resolving ownership gaps, and improving governance and quality. The role leads Data Councils, supports Agile Release Trains, removes data-related blockers, and strengthens data foundations for decision-making, service delivery, analytics, and AI initiatives.

Leads data validation risk initiatives, strategic analytics direction, business development, and complex data quality programs across client engagements. Oversees data collection, preprocessing, modeling, statistical analysis, validation routines, and control-gap assessments. Translates findings into executive recommendations, manages senior client relationships, mentors analytical teams, and advances data governance and AI-enabled analytics while ensuring professional and independence standards.

Develop and improve IP geolocation automation algorithms using large datasets and IP network topology. Query, extract, and transform data with SQL, R, Python, MongoDB, and BigQuery; provide insights that improve data quality; and collaborate with engineers, data scientists, and stakeholders to solve complex problems and lead data science initiatives.

The Quantitative Methodologist will design statistically rigorous studies, apply advanced analytics, interpret results, ensure quality, and communicate insights to clients.

The SI Business Analyst will drive integration between business needs and technical delivery, focusing on insurance and healthcare systems. Responsibilities include capturing requirements, performing gap analysis, designing workflows, and leading cross-functional teams to optimize system performance and support digital transformation initiatives.

Lead marketplace analytics for Affirm’s two-sided ecosystem by optimizing monetization, supply, demand, pricing, profitability, and user experience. Build KPI dashboards, analyze marketplace and affiliate performance, conduct experiments, evaluate incentives and placement, and perform loan-level profitability analyses. Partner cross-functionally with Product, Engineering, Sales, Client Success, and Marketing to improve merchant value, consumer engagement, conversion, and sustainable GMV growth.

Lead Toast’s global People Analytics function across data engineering, analytics, data science, and employee listening. Set the people data and reporting strategy, establish trusted metrics and governance, partner with executives on workforce decisions, measure People program impact with Finance, and build scalable self-service analytics. Manage a distributed US and India team, oversee executive and board-level workforce analysis, and collaborate with privacy, legal, People technology, AI, and data engineering teams.