Top Analytics Jobs in Orlando, FL

Leads data strategy for MetLife’s Group Benefits business by connecting business and Data & Analytics teams, establishing shared definitions, resolving ownership gaps, and improving governance and quality. The role leads Data Councils, supports Agile Release Trains, removes data-related blockers, and strengthens data foundations for decision-making, service delivery, analytics, and AI initiatives.

Leads and manages a business analyst team supporting a data platform. Partners with clients, product managers, engineers, and stakeholders to gather requirements, write user stories, perform data gap analyses and source-to-target mapping, validate data using SQL, and support data quality, lineage, QA, Agile delivery, change management, and documentation. Requires healthcare data expertise, people leadership, strong communication, and experience translating technical information for varied audiences.

Designs and manages enterprise data architectures, models, databases, ETL solutions, catalogs, metadata, and governance practices. Tracks legacy and 1LMx data through an enterprise modernization, ensuring data quality, lineage, retention, compliance, and fitness for reporting and analytics. Coordinates with federated governance teams, records managers, and diverse stakeholders to support transitional architectures and data standardization.

Lead marketplace analytics for Affirm’s two-sided ecosystem by optimizing monetization, supply, demand, pricing, profitability, and user experience. Build KPI dashboards, analyze marketplace and affiliate performance, conduct experiments, evaluate incentives and placement, and perform loan-level profitability analyses. Partner cross-functionally with Product, Engineering, Sales, Client Success, and Marketing to improve merchant value, consumer engagement, conversion, and sustainable GMV growth.

Lead Toast’s global People Analytics function across data engineering, analytics, data science, and employee listening. Set the people data and reporting strategy, establish trusted metrics and governance, partner with executives on workforce decisions, measure People program impact with Finance, and build scalable self-service analytics. Manage a distributed US and India team, oversee executive and board-level workforce analysis, and collaborate with privacy, legal, People technology, AI, and data engineering teams.

Leads strategy, planning, and execution of customer EMR integrations for PhareOS. Oversees end-to-end data delivery, integration quality, process standardization, tooling, vendors, and platform enhancements. Builds and scales the data integration team, manages resources and senior client stakeholders, and drives innovation across integration methods and operating models. Requires extensive healthcare data integration leadership, HL7/FHIR and interface engine expertise, SQL proficiency, and strong program management skills.

Own Eve’s go-to-market data models and semantic layer for governed metrics including pipeline, conversion, CAC, win rate, ARR, and bookings. Establish certification frameworks, modeling standards, documentation, alerting, and analytical application patterns across the organization. Partner with Sales, Marketing, Customer Success, and RevOps stakeholders, resolve conflicting metric definitions, enable AI-grounded data tools, review contributions, and mentor analytics engineers.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Leads enterprise data governance strategy, transformation, operating model modernization, accountability, and executive engagement. Partners with senior stakeholders to improve data trust, accessibility, regulatory alignment, risk management, analytics, AI readiness, and business outcomes. Represents the Data Office in strategic and regulatory forums, establishes roadmaps and performance measures, resolves cross-functional data challenges, and drives organizational change without direct authority. The role focuses on governance and transformation rather than engineering, coding, analytics delivery, or technical administration.

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.

Own Hometap’s product and marketing event-data ecosystem, including taxonomy, tracking plans, governance, Segment Protocols, schema validation, and source management. Partner with marketing, product, and engineering to define instrumentation and event specifications. Build monitoring for schema conformance, event volume, and property completeness, while documenting standards and managing event review and deprecation processes.

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.

Leads an eight-person analytics engineering team and sets strategy for trusted semantic models, governed data, enterprise BI, AI-powered data access, and production data applications. Oversees data modeling, evaluation datasets, telemetry, LLM routing, governance, security, and self-service capabilities. Partners cross-functionally to establish engineering standards, roadmaps, and measurable business impact while hiring, coaching, and developing team members.

Build and maintain scalable analytics data products using SQL, dbt, Snowflake, and dimensional modeling. Design trusted warehouse tables, semantic layers, metrics, dashboards, and self-service tools for BI, data science, machine learning, and AI use cases. Partner with stakeholders, optimize performance and costs, enforce data governance and privacy, improve data discovery and lineage, and mentor teammates through collaborative development and code reviews.

Analyze lifecycle marketing performance, develop measurement and attribution frameworks, optimize campaigns and customer journeys, and connect marketing activity to product and business outcomes. Partner with marketing, product, engineering, and data teams to improve analytics capabilities, use AI-powered techniques for predictive insights, and present recommendations to senior leadership.

Owns sales and creator-commerce data end to end, building tested and documented dbt models, semantic-layer metrics, and Omni dashboards. Partners with Sales, RevOps, Product, and data engineering to model CRM, pipeline, funnel, commerce, and product-usage data. Establishes trusted metric definitions, improves self-service reporting, enables AI-assisted data querying, reviews code, documents decisions, and serves as the primary owner of Kit’s sales data domain.

Own the architecture, technical direction, reliability, and evolution of a shared cloud data platform. Lead hands-on development of streaming and batch pipelines using infrastructure-as-code, build governed analytical data products, and establish data contracts, quality, security, lineage, and observability standards. Serve as the final technical escalation point, mentor engineers, lead design and code reviews, promote responsible AI-assisted coding, respond to incidents, and communicate technical tradeoffs across stakeholders.

Leads a category insights team supporting client and retailer strategies. Analyzes shopper, consumer, market, pricing, promotion, assortment, and competitive data to create compelling selling stories and inform go-to-market decisions. Manages client engagements, business reviews, project schedules, and associate development while coaching analysts and collaborating with sales and external stakeholders.

The Senior Manager of Risk Analytics will lead credit risk strategies, manage portfolio performance, optimize decisioning frameworks, and drive business growth through analytics and predictive modeling.

The Senior Manager leads Power BI reporting and analytics functions, overseeing a team and ensuring standardized, scalable reporting solutions while managing transition to Microsoft Fabric.

Leads advanced data analytics and engineering initiatives, including data infrastructure, ETL, pipelines, warehousing, governance, visualization, and AI-enabled solutions. Supervises analysts, manages data systems and Smartsheet workflows, ensures documentation and contract compliance, and delivers insights, reports, and recommendations to improve program operations and grant management.

Own the analytics function supporting fraud, credit risk, and operations. Build automation, reporting infrastructure, fraud-rule backtesting frameworks, risk-label systems, dashboards, and AI-assisted tools. Partner with stakeholders to identify high-impact opportunities, reduce manual work, and track hours saved. This hands-on individual contributor role has managerial scope and includes defining a new analytics function.

Designs and maintains scalable data pipelines, integrations, and foundational data models using Snowflake, dbt, and AWS. Establishes data quality, testing, governance, and documentation standards while supporting analytics, financial systems, and reporting. Partners with Engineering, Analytics, Finance, and Operations, leads technical decisions, improves development workflows, mentors teammates, and incorporates AI coding agents into engineering processes.

Leads the development of scalable business intelligence, reporting, dashboards, data governance, and analytics capabilities. Integrates syndicated CPG, loyalty, inventory, and store-level data to generate actionable commercial insights. Partners with Consumer Insights and cross-functional leaders, manages external data providers, improves data quality, and helps implement AI-enabled reporting and analytical workflows. Requires strategic leadership combined with hands-on data, BI, and stakeholder engagement.

Leads operational analytics and reporting for Business Operations, including recurring performance reporting, KPI development, dashboards, data validation, root-cause analysis, and actionable insights. Partners with cross-functional leaders to improve performance management, reporting automation, data quality, and decision-making. Builds and develops a high-performing analytics team while connecting operational metrics to customer experience, productivity, service, revenue, and cost.