Top Senior Analytics Jobs in Tampa, FL

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 a client-facing healthcare analytics team that designs and maintains prior authorization decision automation programs. Consults PaaS clients, develops strategic roadmaps, translates requirements into technical blueprints, analyzes authorization and claims data, and builds KPI reports using visualization tools. Manages direct reports, improves analytics processes and AI tooling, partners with product and engineering teams, and ensures automation outcomes and client KPIs are achieved.

Designs and maintains scalable data infrastructure, ETL/ELT pipelines, canonical datasets, and AI context layers. The role improves data quality and alignment across sales and finance systems, investigates data inconsistencies, leads requirements through UAT and implementation, supports analytics self-service, and partners with cross-functional teams to deliver process improvements and reliable business data.

Leads business and data analytics strategy for P&C pricing, serving as a liaison between pricing, actuarial, business, and technology teams. Oversees data platforms, reporting, governance, analytics delivery, requirements gathering, portfolio prioritization, and strategic initiatives. Provides thought leadership, manages risks and capacity, influences senior stakeholders, and guides teams in delivering scalable data solutions that support business decisions and policy modernization.

Leads pricing and product analytics strategy for Auto and Property teams. Develops strategic plans, business cases, analytical frameworks, and outcome measures; evaluates profitability, pricing, risk, marketing, sales, and member experience insights. Influences executive decisions through quantitative and qualitative analysis, storytelling, and stakeholder engagement. Establishes operational processes, tracks initiatives, mentors team members, and ensures compliance with risk policies.

Build Deepgram’s governed decision layer above warehouse gold tables. Responsibilities include modeling cross-system entities, owning semantic and metrics definitions, creating agent-facing data tools and MCP surfaces, implementing data quality assertions and reconciliation checks, evaluating AI agent accuracy, and answering business questions while leaving reusable models behind. The role requires production-grade SQL and Python, semantic-layer ownership, strong data modeling judgment, AI-native workflows, clear writing, and comfort building infrastructure from scratch.

Develop and maintain scalable data pipelines, models, datasets, reports, and dashboards for operational reporting. Use dbt, Airflow, Azure Data Factory, SQL, Power BI, and related technologies to build, optimize, test, migrate, and support data delivery solutions. Collaborate with technical and business stakeholders, conduct root cause analysis, automate maintenance, contribute to development standards, and mentor junior engineers. The role requires P&C insurance experience and hybrid work three days per week at a specified office location.

Leads business intelligence and analytics for Verizon’s Business Markets Group. Designs measurement programs, develops advanced geospatial and financial models, evaluates sales and operational approaches, standardizes metrics, and converts complex data into strategic insights. Partners with business, technology, marketing sciences, and operational analytics teams while leading cross-functional data initiatives.

Leads the design, development, testing, tuning, and optimization of financial crimes detection models across AML, fraud, KYC, and sanctions. Performs statistical analysis, threshold calibration, back-testing, model efficacy assessments, feature engineering, and root cause analysis. Configures financial crimes platforms, monitors model performance, establishes testing and governance standards, and partners with Model Risk Management and leadership on validation, audit, regulatory, and risk-related initiatives.

Leads enterprise data and analytics strategy, architecture, modernization, and delivery across cloud and on-premises environments. Oversees data platforms, engineering, integration, governance, quality, lineage, security, and compliance. Partners with executives to define roadmaps and investments, manages cross-functional teams and vendors, enables AI/ML capabilities, and mentors data professionals while driving scalable, trusted data solutions and measurable business outcomes.

Leads healthcare data analysis, reporting, dashboard development, forecasting, and data-quality processes. Analyzes claims, utilization, cost, pharmacy, and financial data to identify trends and support cost-containment and business decisions. Develops SQL database objects, translates stakeholder requirements, supports regulatory reporting, improves analytics workflows, and manages projects. Provides mentoring, peer review, documentation, and cross-functional guidance.

Owns end-to-end customer analytics workstreams, including KPI frameworks, multi-source dashboards, reporting, data governance, quality assurance, and insight delivery for government digital communications programs. Presents recommendations to stakeholders, mentors junior analysts, leads Agile ceremonies, documents analytics practices, resolves data issues, and evaluates AI-assisted analytics tools.

Analyze startup user and product data, identify trends and drivers, and turn findings into strategic recommendations. The role owns key metrics and dashboards, leads analytical deep dives, sizes opportunities, evaluates product tradeoffs, supports roadmap prioritization, and develops external-facing insights about startups in partnership with marketing and communications.

Manages programmatic analytics and insights for client accounts, leading measurement frameworks, brand lift studies, incrementality testing, and A/B experiments. Develops media and campaign strategies, communicates performance insights to clients, and supports pitches and QBRs. Oversees, mentors, and develops analysts while partnering with Product, Engineering, Sales, and Customer Success teams to improve measurement tools, campaign optimization, and analytical capabilities.

Leads enterprise sanctions-screening analytics strategy, developing KPI frameworks, governance standards, dashboards, root-cause analyses, and predictive insights. Identifies false-positive drivers, workflow bottlenecks, and automation opportunities while recommending tuning and process improvements. Partners with technology, operations, compliance, and governance stakeholders to build business cases, implement analytics-enabled automation, monitor performance, and deliver executive-ready reporting.

Build and scale secure data lakehouse and warehouse infrastructure supporting analytics, machine learning, clinical AI performance monitoring, and self-service insights. Develop scalable data pipelines, models, orchestration, quality controls, and LLM-enabled analytics tools using heterogeneous clinical and EHR data. Collaborate with engineering, data science, clinical, product, and client success teams to establish trustworthy metrics and technical solutions.

Designs and optimizes Power BI dashboards, semantic models, datasets, DAX measures, and reporting solutions for identity governance and administration analytics. Partners with ETL engineers and stakeholders to validate Parquet data from Azure Synapse and SailPoint sources, establish data-quality checks, monitor refreshes, define KPIs, and document data lineage. Supports compliance reporting, access governance, audit readiness, certification metrics, and Zero Trust analytics.

Lead a team delivering product and business analytics for Fetch's commerce and shoppable experiences. Own prioritization, experimentation, measurement, KPI dashboards, and stakeholder-facing insights to inform product, marketing, and commercial decisions. Manage and develop analysts while partnering cross-functionally to ensure data quality, repeatable analyses, and actionable recommendations.

Lead the architecture and development of enterprise analytics models, dbt transformation pipelines, semantic layers, and BI datasets. Apply dimensional modeling, data governance, quality testing, observability, and performance optimization to deliver trusted business data. Partner with executives and cross-functional teams, standardize metrics, improve legacy workflows, support AI/ML integrations, and mentor engineers. Own key domain models and contribute to the analytics platform roadmap as a technical leader.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, campaign reporting, experimentation, and lifecycle analysis. Partners with Marketing and Finance to connect performance metrics to business goals, automate reporting, and generate actionable insights. Builds churn, retention, segmentation, and LTV models while evaluating paid acquisition and customer growth opportunities using SQL, Python, BI tools, marketing platforms, and modern AI-enabled workflows.

Owns fraud performance analytics for depository products, including monitoring losses, approval rates, false positives, customer friction, and risk metrics. Builds data models, transformation pipelines, dashboards, scorecards, and monitoring frameworks. Conducts fraud deep dives and develops optimized rules, policies, thresholds, models, and decision strategies. Partners with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk teams to improve fraud detection and support product launches.

Own the analytics data layer by translating stakeholder needs into certified dimensional models, governed metrics, semantic layers, dashboards, and reports. Build with dbt, SQL, Databricks, Power BI, and Airflow while ensuring data quality, observability, reconciliation, documentation, and dependable orchestration. Partner closely with finance, operations, and client-facing teams, automate recurring workflows, and use AI-assisted engineering practices in a fully remote environment.

Leads Navitus’s centralized analytics team, delivering client performance analysis, financial modeling, underwriting support, pricing analysis, competitive intelligence, dashboards, and strategic recommendations. Partners with Sales, Finance, Clinical, Network Strategy, Account Management, and technical teams to support client growth, retention, RFPs, renewals, and market-facing engagements. Establishes data quality and governance standards, improves analytical processes, and mentors team members.

Leads advanced analytics across the organization, owning MAU forecasting and growth models, experimentation standards, and causal inference methods. Establishes analytical best practices, reviews high-stakes analyses, partners with data and product teams, and scales recurring work through AI tooling. Mentors data professionals and translates complex statistical findings into actionable leadership recommendations.