Top Analysis Reporting Jobs in Philadelphia, PA

Design and execute advanced statistical and data analyses for client projects, using tools such as R, Tableau, SAS, VBA, and Excel. Translate data into actionable insights, communicate findings to clients and internal teams, collaborate on solution implementation, and take ownership of project deliverables.

Supports data analysis projects in PwC’s Advisory practice, researching datasets, identifying patterns, integrating data, and creating dashboards and visualizations with Alteryx and Power BI. Assists with algorithm development, analytics automation, and data-driven insights for clients. The internship emphasizes learning PwC methodologies, collaborating with experienced professionals, and gaining exposure to AI, cloud platform design, and data architecture.

Supports client-facing diligence analytics projects by gathering, integrating, and analyzing data; developing data-driven insights; creating dashboards and reports; conducting research and data mining; contributing to algorithm development; and preparing presentations. The intern uses Alteryx and Power BI, collaborates with advisory teams, and gains exposure to cloud platforms, data architecture, data science, and AI applications.

Supports data analysis and analytics projects through research, data gathering, dashboard creation, data integration, data mining, algorithm development, and data validation. Uses Alteryx and Power BI to automate workflows and report metrics while contributing to client-focused insights. The intern will learn PwC methodologies, collaborate with experienced professionals, and develop skills in data visualization, cloud platforms, data architecture, and artificial intelligence.

Design and deliver end-to-end web applications and data pipelines that integrate enterprise systems (including Oracle). Build high-performance data models, dashboards (Power BI), REST APIs, and UI components. Integrate tools like Jira and Smartsheet, implement logging/instrumentation (ELK), and collaborate in Agile to provide documentation, training, and ongoing support.

Leads international CRM decision intelligence, translating customer, campaign, and market data into strategy and next-best-action recommendations. Oversees predictive analytics, segmentation, measurement, dashboards, data quality, privacy, opportunity sizing, and AI-enabled insight generation across global markets. Partners with CRM, data, AI, digital, commercial, legal, and compliance teams to scale trustworthy personalization and analytics.

Lead a team evaluating new and existing data assets, standardize due-diligence and analytical methodologies, validate data quality and business value, partner with Product and Technology to support onboarding and OneTru cataloging, establish governance and lineage standards, and coach team members to drive data-driven product and revenue decisions.

Analytics interns will research company data, write analytical code, uncover insights, and communicate actionable recommendations to leadership. Interns may join Strategic Analytics, Risk, or Business Planning & Analysis teams, collaborating in a fast-paced fintech startup. The 10–12-week program includes mentorship, data challenges, team interviews, and opportunities to support business decisions.

Provides technical leadership for Finance, Actuarial, and Corporate Data platforms. Defines engineering strategy and standards, architects automated data pipelines, leads cloud migrations and ETL modernization, and drives AI-assisted development, DevOps, CI/CD, testing, and data quality practices. Manages senior data engineers and distributed teams, resolves complex engineering issues, governs technical delivery, and communicates strategies to executive stakeholders. Requires extensive enterprise data engineering, cloud platform, data warehousing, automation, and people leadership experience.

Provides technical leadership for enterprise lakehouse architecture and data foundation initiatives. Designs and develops scalable batch, streaming, and event-driven pipelines using Databricks, AWS, Spark, Python, SQL, and Delta Lake. Establishes engineering standards for modeling, testing, CI/CD, quality, observability, governance, and support. Translates business needs into architecture decisions and delivery plans, coordinates contractors and vendors, mentors engineers, and partners with product, supply chain, governance, and AI/ML teams.

Leads DePuy Synthes’ corporate Data and AI strategy across ERP, HR, Legal, Procurement, Finance, and Corporate Affairs. Owns demand management, prioritization, governance, roadmaps, and delivery portfolios while coordinating global delivery teams. Oversees data products, dashboards, analytics, predictive models, and AI solutions; advances data governance, master data management, and data quality. Builds stakeholder alignment, tracks business value, and develops data and AI talent across a global matrixed organization.

Leads DePuy Synthes Supply Chain’s Data and AI strategy, demand prioritization, governance, roadmap, and portfolio delivery. Partners with business, IT, and global capability center teams to deliver data products, dashboards, predictive models, and AI solutions across planning, procurement, manufacturing, inventory, logistics, and customer service. Establishes data quality and value-realization frameworks, manages executive stakeholders, and develops data and analytics talent.

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.

Develops scalable, secure ETL pipelines, database architectures, and real-time or batch data solutions. Integrates large datasets, ensures data quality and integrity, writes complex code and queries, and translates business needs into technical designs. Leads solution development, testing, releases, documentation, training, and vendor issue resolution while advising business partners on data analysis and tools.