Top Senior Analysis Reporting Jobs in Philadelphia, PA

Leads the Underwriting Data Engineering team and oversees the design, development, and productionization of scalable data and machine learning pipelines. Responsibilities include feature engineering, data preparation, model deployment, data validation, governance, monitoring, API integration, analytic data products, roadmap development, stakeholder collaboration, and team coaching.

Designs, develops, and owns business intelligence dashboards, visualizations, analyses, and reporting solutions, primarily in TIBCO Spotfire and also Power BI. Responsibilities include data modeling, calculations, performance tuning, deployment workflows through GitHub, data quality collaboration, BI standards, risk identification, mentoring, and independent decision-making across a multi-tenant Life Sciences data platform.

Leads the design and maintenance of automated data systems for insurance commission processing, accounts payable, payroll reconciliation, and agency payments. Builds ingestion, validation, normalization, reconciliation, mapping, encryption, and self-service tools. Manages agent and agency master data and cloud-hosted infrastructure with backup and recovery capabilities. Improves financial operations by replacing manual spreadsheet workflows with secure, scalable, auditable pipelines.

Analyze technology spending, cost drivers, portfolio performance, operational metrics, and technology initiatives. Develop executive dashboards and reporting, synthesize complex data into actionable insights, monitor risks and dependencies, and support governance, planning, and decision-making. Partner with technology, finance, and business stakeholders while contributing cybersecurity knowledge, financial analysis, and technology governance expertise.

Lead client solution onboarding for alternative investment services, including estimation, solution design, system configuration, reporting, data conversion, automation, testing, and process improvements. Translate business requirements into technical specifications and manage custom reporting and file extract projects. Analyze client requests, develop end-to-end test cases, and collaborate with developers, QA, fund accountants, investor services, relationship managers, and external stakeholders to deliver and maintain solutions.

Designs, builds, administers, and troubleshoots cloud data architectures, databases, schemas, metadata repositories, ETL processes, and analytic models. Ensures data integrity and quality, develops SQL queries and reports, leads testing and automation improvements, and supports dashboards, governance, data sharing, and metric collection. Collaborates with Agile teams to translate business requirements into technical infrastructure designs and decision-support capabilities using AWS, Java, Python or Scala, GitLab, and Terraform.

Leads Data Operations, including reporting, dashboards, data warehouse and dbt model oversight, data quality, governance, service levels, incident response, and stakeholder prioritization. Manages and develops data professionals while partnering with Data Engineering, Security, Privacy, Compliance, and Enterprise Architecture. Ensures reliable, secure, well-documented data services and protects PHI through appropriate access, privacy, lineage, retention, and monitoring controls.

Analyze executive questions using financial, operational, sales, and customer data; reconcile inconsistent sources; build models and variance analyses; deliver recommendations and board-quality reporting. Lead cross-functional CEO initiatives, support acquisition integration and diligence, coordinate executive office continuity, and manage confidential information. Create visualizations, project plans, executive presentations, and reporting architecture while partnering with senior leaders across finance, operations, IT, and corporate functions.

Leads the Marketing Analytics function and team, setting strategy, operating models, measurement frameworks, and analytics priorities. Advises executives on customer acquisition, marketing investment, and commercial strategy through actionable insights. Oversees experimentation, KPI reporting, data quality, governance, AI adoption, and cross-functional collaboration with Marketing, Product, Finance, Operations, Data Science, and Engineering.

Advance investment data, reporting, and technology capabilities by designing scalable data pipelines, monitoring and resolving data exceptions, building reports and dashboards, supporting product management and UAT, improving automation and governance, and partnering cross-functionally to maintain data quality and documentation.