Top Fintech Data & Analytics Jobs in Philadelphia, PA

The Pricing Analyst III develops pricing models and performs analysis in mortgage insurance pricing, presenting findings to senior leadership.

The role involves developing data analytics strategies, enhancing business intelligence, ensuring data integrity, mentoring junior analysts, and adopting innovative data solutions.

Assist in consulting engagements focusing on financial analysis, data modeling, and litigation support. Involves analysis of large datasets and financial documentation.

Lead strategic data evolution for Fund Administration clients, building dashboards, managing stakeholders, and translating business needs into actionable insights.

Seeking a Financial Market Analyst to conduct market research, produce analysis and reports, represent the company in media, and collaborate with internal teams to align market insights with strategic goals.

Lead fraud detection and mitigation for a conversational BNPL product. Define fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, collaborate on ML models and decisioning workflows, and coordinate SARs and compliance reporting.

Lead fraud risk for a conversational lending product (SNPL): define first-party fraud typologies, analyze repayment and chargeback trends, own fraud KPIs, design automated/manual blocking policies, coordinate ML/rules with central Fraud and Data teams, and liaise with Compliance on SARs and loan abuse.

The Product Data Analyst leads data collection and analysis to inform product strategy, collaborates across teams, and ensures data integrity for decision-making in product management.

Design, build, and maintain cloud-based big data platforms, pipelines, and tools. Lead scrum teams, implement CI/CD and IaC, apply TDD/BDD, mentor peers, and deliver reliable data processing, quality, and governance solutions to solve risk-related business problems.

Lead architecture and delivery of Boulevard's data platform, building foundational data models, pipelines, and customer-facing analytics. Collaborate with Product and Engineering to create scalable data products, Snowflake data sharing solutions, performant visualizations, and machine learning features (recommendations, forecasting, anomaly detection) to drive data-driven decision-making and product value.

Lead the analytics team for the third-party agent business, driving business strategy, product analytics, and AI-powered insights while fostering cross-functional partnerships.