Top Data & Analytics Jobs in Philadelphia, PA

The Data Architect is responsible for designing and implementing data architecture strategies, developing data pipelines, and ensuring compliance with data governance policies. They collaborate with stakeholders to deliver effective data solutions and lead cloud-based implementations.

As a Data Analytics Senior Consultant at CNA, you will lead projects to create automated scorecards and scenario analysis tools, provide business insights based on data analysis, collaborate with underwriting leadership, and develop analytics solutions that enhance business strategies across commercial insurance products.

As a Senior Associate, you will oversee clinical data management for trials, ensuring the accuracy and integrity of data. Responsibilities include data preparation, creating data management plans, setting up data reviews, and collaborating with stakeholders to improve processes and learning from studies.

The Sr. Data Analyst will analyze data sets, conduct research projects, and validate customer tests. Responsibilities include creating SQL queries, troubleshooting data issues, and communicating findings effectively. This includes engaging with internal technical teams and external business groups to ensure expectations are met, and maintaining reports for management and operational teams.

As a Data Scientist at CoreWeave, you will help evolve the company’s product databases, forecast demand trends, and develop solutions for analytic problems. You’ll contribute to metrics and reporting, ensure data integrity, and support capacity planning models for decision-making.

The CMBS Analyst will monitor and assess CMBS transactions, perform cash flow analyses on commercial properties, derive property valuations, maintain surveillance on a CMBS portfolio, and contribute to research reports.

The Data Scientist will enhance organizational performance through innovative analytics models and processes. Responsibilities include collaborating with business stakeholders to identify opportunities for analytics solutions, conceptualizing and designing models to address business problems, sourcing data with Data Engineers, and fostering data science capabilities within teams.