Top Analysis Reporting Jobs in Orlando, FL

Support and advance rating tools, conduct technical analyses for insurance pricing, manage portfolio performance, and mentor junior analysts.

The Facets Systems Analyst will perform development and maintenance tasks in Facets, lead a team of developers, and ensure quality outcomes through testing methodologies while maintaining compliance with healthcare standards.

The Business Operations Analyst will centralize and improve corporate reporting and business intelligence while executing data acquisition for patient data initiatives. Responsibilities include metric compilation, dashboard design, and data analysis across multiple teams.

As a Senior Data Scientist, you will lead data initiatives by setting goals, architecting data models, enhancing data quality, and mentoring team members to drive impactful business decisions at SmithRx.

The Risk & Fraud Analyst II monitors fraud alerts, investigates cases, assesses risks, collaborates with stakeholders, and improves risk processes.

As a Data Analyst at Solace, you will drive operational excellence by identifying inefficiencies, build scalable analytics systems, and communicate data insights to help the business scale effectively.

Lead design, planning, execution, and quality oversight of clinical trial data management (Phase I-IV). Manage CROs and vendors, ensure EDC/eCRF/ CDM standards, support database locks/snapshots, collaborate with Biostatistics/Programming and other functions, and maintain regulatory-ready documentation for submissions.

As a Staff, Advanced Analytics, New Business, you'll analyze data for new business extensions, collaborate with teams, define metrics, and conduct A/B tests to drive strategic decisions.

Join Nextdoor's machine learning team to build data-intensive products, develop ML models, analyze datasets, and enhance user experiences. Collaborate closely with product and data science teams.

Lead design, build, and optimization of Sezzle's large-scale data warehousing and pipelines. Own data infrastructure KPIs/SLAs, improve Redshift performance, evolve the data stack, implement ETL/ELT workflows, and partner with cross-functional teams to deliver reliable, scalable datasets.