Top Analysis Reporting Jobs in Philadelphia, PA

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 client-facing data validation and risk workstreams, developing reliable data pipelines, integrations, transformations, and validation controls. Manages project plans, budgets, timelines, deliverables, and team performance while analyzing data structures and system interactions to identify risks. Coaches team members, collaborates with stakeholders, improves database and query performance, promotes automation and AI-enabled tools, and ensures technical standards, documentation, and independence requirements are maintained.

Owns data systems workstreams for public fixed income investment operations. Leads process improvement and automation, develops reports, dashboards, and data models, manages data quality and issue resolution, and performs portfolio analysis, forecasting, benchmarking, and financial modeling. Partners with investment, client, and business teams on reporting and analytics while supporting technology implementations, translating business needs into technical requirements, and mentoring junior analysts.

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.

Leads the design and modernization of scalable data architecture for economic data platforms, including massive time-series datasets, archival documents, and research publications. Responsibilities include data modeling, metadata and governance design, storage and processing architecture, indexing, discoverability, security, lifecycle management, and API data access optimization. Partners with application architecture and cross-functional teams to deliver highly available, secure, public-facing data platforms supporting analytics and research.

Leads commercial analytics strategy and client storytelling for pharma and agency partners. Translates campaign measurement, media mix, healthcare datasets, and cross-brand trends into actionable recommendations that support sales, renewals, product positioning, and client outcomes. Serves as a senior thought partner and public-facing industry voice, presenting data-driven insights to executive stakeholders and conferences while collaborating with Sales, Marketing, Product, and Campaign Measurement teams.

Lead the redesign and modernization of a legacy database system for a financial services client. Analyze existing architecture, design scalable data models and schemas, optimize tables and stored procedures, implement governance and security controls, and ensure performance, auditability, and regulatory compliance. Partner with stakeholders in an Agile environment, support iterative development, and mentor team members on database modeling best practices.

Manages data strategy and analytics for digital media clients, developing measurement roadmaps, advanced analyses, statistical tests, and strategic recommendations. Owns client data technology stacks, translates complex findings into client-ready narratives, partners with media platforms, and mentors analysts. The role involves data clean rooms, modeling, campaign measurement, audience insights, visualization, adtech, and direct client communication.

Builds scalable data pipelines and infrastructure supporting AI and machine learning algorithms, including large language models, NLP, and time-series analytics. Responsibilities include data extraction, transformation, loading, normalization, curation, automation, dashboard development, and process improvement. The role also implements AI/ML algorithms and uses Agile software development practices while requiring an active TS/SCI clearance and willingness to obtain a CI or full-scope polygraph.