Top Data & Analytics Jobs in Miami, FL

Lead and build PushPress's data and AI foundation: define data strategy, architect pipelines and warehousing, ensure data quality and governance, enable AI product features, deliver analytics and reporting, and hire and grow a high-performing data team.

Execute financial models and pharmacy claims analyses to support underwriting for sales bids, present results to stakeholders, recommend pricing adjustments, drive pricing research, improve processes, and run quality control on analyses.

Analyze on-chain trading activity and market/DEX/CEX data at scale, build models for portfolio/PnL and capital efficiency, design AI-driven research pipelines, produce insights to inform product and capital strategy, and collaborate with product and engineering teams.

The Senior Product Analyst will analyze complex data sets to guide product strategies, support game teams, and drive game performance insights through collaboration and robust reporting on game features.

Design and execute advanced analytics and statistical models to support revenue cycle surveillance and risk monitoring. Extract, validate, reconcile, and integrate MHS GENESIS and enterprise repository data. Develop and optimize SQL/Vertica queries, CCL/Discern extracts, dashboards (Power BI, Tableau, SAP BO), and analytic deliverables. Support backend diagnostics, incident/change management, remediation analysis, and stakeholder briefings while ensuring HIPAA and federal data governance compliance.

As an Operations Analyst, you'll develop scalable reporting, model supply and demand, and engage with stakeholders to inform business strategies across markets.

Drive go-to-market revenue analytics and strategy by building forecasts, dashboards, and ad-hoc analyses. Partner with Sales, Sales Ops, and Finance to set targets, quota, and deliver actionable recommendations to executive leadership.

The role involves collecting, analyzing, and visualizing data for investment research, utilizing web scraping, data tools, and data science techniques.

Develop and maintain datasets for visualization and machine learning; automate data pipelines; partner with teams to build data products.

Design and execute HEOR studies (cost-effectiveness, budget impact, real-world evidence) using large claims datasets; collaborate cross-functionally; engage stakeholders; produce scientific deliverables (abstracts, posters, manuscripts); and communicate HEOR insights to support adoption, access, and reimbursement for genetic testing services.