Top Data & Analytics Jobs in Miami, FL

Build and maintain Databricks data pipelines using SparkSQL and PySpark; ingest, transform, model, and validate data from payer, provider, claims, platform, and API sources. Support automated file exchanges, dashboards, testing, data governance, access controls, and audit logging. Use AI coding agents responsibly, participate in design and code reviews, document technical decisions, and collaborate with business teams. The role is based in Miami and targets candidates graduating between December 2026 and June 2027.

Leverage data analytics, business intelligence, and Python to deliver strategic insights and tailored solutions for clients. Build reports, dashboards, data pipelines, and support data architecture and quality initiatives. Analyze data from multiple sources to identify trends, improve operations, and inform decision-making. Collaborate with stakeholders and team members while continuously developing technical skills and contributing to process improvements.

Develop and improve mathematical models and trading approaches. Conduct statistical analysis and back test trading strategies in a fast-paced environment.

Conduct quantitative research for automated trading strategies by developing mathematical models, translating algorithms into code, backtesting trading signals, analyzing unconventional data, and refining monetization systems. Collaborate with senior researchers during an 11-week post-doctoral internship while applying advanced probability, statistics, machine learning, and time-series techniques to financial markets.

Designs and maintains dashboards, reports, semantic views, data models, pipelines, and analytical workflows supporting Finance and Accounting. Partners with stakeholders to define metrics, build trusted BI solutions, investigate data issues, automate workflows, and deliver recurring and ad hoc insights. Requires strong SQL, Tableau or similar BI experience, Python, data validation, pipeline support, and effective communication with technical teams and executives.

Design and scale lakehouse architecture, streaming and batch pipelines, and reliable data platforms using Kafka, Spark, Airflow, Iceberg, Databricks, and related technologies. Build Medallion-layer data systems, manage open table formats, optimize distributed queries, monitor platform reliability, resolve data quality issues, and collaborate with analysts, data scientists, and product teams.

As a Senior+ Agentic Analytics Engineer, you will design and deploy AI systems that provide actionable insights, build analytics tools, and manage the analytics-to-action pipeline to drive business decision-making using AI.

Performs advanced data analysis, predictive modeling, reporting, dashboard development, and database design for Population Sciences research. Oversees data quality, governance, compliance, participant accrual tracking, and reporting across REDCap, Velos, and other systems. Provides actionable insights, supports NCI reporting, improves data processes, and advises less experienced analysts while serving as a central data resource for investigators and leadership.

Design, optimize, and maintain scalable data architectures, pipelines, and processing solutions. Ensure data quality, perform SQL and Python analysis, build dashboards and visualizations, and support marketing and product analytics. Lead tooling development, requirements gathering, QA, stakeholder communications, and cross-functional initiatives while providing technical guidance and managing team decisions.

Designs, governs, validates, and deploys enterprise ontologies, taxonomies, vocabularies, and knowledge graphs. The role translates business domains into standards-compliant semantic models, maps structured and unstructured data, supports reasoning and analytics, and collaborates with engineering, AI/ML, product, and business teams. Responsibilities include stakeholder workshops, competency-question development, ontology governance, SHACL/ShEx validation, R2RML/RML integration, and coaching junior team members. The position is hybrid and requires 20–80% travel to client locations.

Reviews and validates music royalty statements, investigates data inconsistencies, and converts financial reports into standardized datasets. Builds Python automation tools, improves processing accuracy and scalability, monitors operational metrics, and collaborates with Engineering, Finance, Investment, Research, and Product teams to support pricing and underwriting decisions.