Top Remote Data & Analytics Jobs in Orlando, FL

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Develop and support enterprise business intelligence and data solutions using Power BI, Microsoft Fabric, Power Query, DAX, SQL, automation, and AI technologies. Responsibilities include data transformation, modeling, visualization, reporting, governance, integration, semantic model development, and citizen development enablement. The role collaborates with business and technical teams, mentors users, supports enterprise data architecture, and promotes scalable, secure, high-quality BI practices.

Provides advanced analytics for enterprise business operations and transformation initiatives. Responsibilities include data extraction, modeling, reconciliation, KPI development, process intelligence, business-case validation, reporting, data-quality audits, and value-realization tracking. The role communicates insights to senior stakeholders, supports data-driven decisions, mentors analysts, and may assist with workload planning and project implementation. Healthcare-related analytics experience is preferred.

Leads business intelligence consulting and analytics for external clients. Designs scalable dashboards, reports, visualizations, automated reporting solutions, and data processes using disparate datasets. Identifies trends, resolves complex data issues, and delivers actionable recommendations through executive presentations. Manages client relationships, documentation, reporting support, and analytics governance while mentoring junior employees.

Uses patent data and analytics expertise to define, evaluate, and improve AI-assisted patent intelligence products. Responsibilities include creating evaluation standards, reviewing AI outputs, identifying data and reasoning issues, shaping product use cases, collaborating with engineering and product teams, and presenting recommendations to senior stakeholders. The role supports portfolio comparison, competitor benchmarking, technology trends, licensing, M&A, patent summaries, and claim interpretation.

Analyzes data from multiple sources to identify trends, develop member segmentation and lifecycle models, support competitive analysis, and recommend strategies for improving member participation and financial products. Builds reports, dashboards, and data-driven tools for leaders and staff, collaborates with stakeholders, trains power users, and provides ongoing analytical support using SQL, R or Python, ETL, data modeling, and business intelligence tools.

Lead the technical direction, architecture, reliability, observability, and modernization of a cloud-based data engineering platform. Design scalable pipelines and reusable frameworks supporting analytics and AI, improve data quality, and establish testing, code review, CI/CD, and engineering standards. Drive adoption of AI-assisted development tools and build agentic workflows across planning, coding, testing, and deployment. Partner with machine learning, MLOps, Analytics Engineering, and business stakeholders in a highly autonomous senior individual contributor role.

Analyzes ESHS and sustainability data, maintaining analytics pipelines and developing dashboards, KPI reports, predictive models, and data-governance standards. Uses statistics, machine learning, and AI to evaluate program performance and identify corrective actions. Partners with subject matter experts, AI teams, and cross-functional stakeholders to translate business needs into data-driven solutions, communicate executive insights, and support enterprise analytics strategy and adoption.

Analyzes healthcare and business data from multiple sources to create reports, dashboards, forecasts, and actionable insights. Develops SQL- and Excel-based reporting solutions, validates data quality, supports claims and utilization analysis, fulfills regulatory reporting requirements, and improves reporting workflows. Collaborates with stakeholders to define requirements, presents findings, documents methodologies, and supports analytics projects, audits, and process automation.

Analyze customer lifecycle and Customer Success data to measure attribution, campaign performance, product adoption, retention, and revenue impact. Build multi-touch attribution models, integrate digital engagement data with Gainsight and CRM events, clean and unify datasets, segment audiences, identify journey bottlenecks, and create Tableau or Looker dashboards. Partner with Campaign Strategy, Product Insights, and CS Operations teams to deliver actionable recommendations and improve automated and human customer interventions.