Top Senior Analytics Jobs in Tallahassee, FL

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Lead and build a product analytics function: define KPI framework, instrumentation, and self-serve analytics using Pendo and BI tools. Partner cross-functionally to measure product performance, surface insights, influence roadmap and embed AI-powered analytics into product lifecycle.

Lead a team of analysts and data scientists embedded in sales to build rigorous pilot analyses, create executive-ready business cases, expand consultative analytics across the partner lifecycle, and publish industry insights while coaching and scaling the Solutions Analytics function.

Bridge enterprise customers' legacy BI to Hightouch by reverse-engineering complex marketing reports, building reusable reporting frameworks, engineering and documenting semantic/context layers, ensuring accurate SQL generation, and training non-technical marketers while collaborating cross-functionally to deliver reliable, idempotent AI-driven analytics.

Lead full-stack analytics at Air by designing and maintaining dbt models and BigQuery transformation layer, ensuring data quality and observability, owning ingestion/orchestration, building self-serve BI (Mode/Hex) and AI-native interfaces, and partnering with product, growth, and GTM teams to deliver trusted data products and strategic insights.

Build and maintain dbt data models, design BI dashboards and reports (Count and other tools), and deliver merchant/issuer analytics. Partner with GTM and product teams to translate data into actionable insights, improve data quality, and lead technical investigations to scale analytics infrastructure.

Own and evolve the analytics engineering platform: design and maintain certified dbt models, enforce modeling/testing/documentation standards, build semantic and metadata layers, optimize Snowflake performance, partner with analysts and data engineering to migrate business logic and ensure reliable, AI-ready analytics, and mentor teammates on analytics engineering best practices.

Contract Google Analytics specialist to audit, implement, and optimize GA4 and GTM setups, build Looker Studio dashboards, integrate CRM data, deliver insights and client trainings, and support short-term marketing analytics engagements.

Lead architecture and delivery of enterprise data transformation on the Guidewire Data Platform. Drive design, ingestion/egress, migration performance, and AI-enabled tooling. Facilitate inception and design review sessions, mentor teams, coordinate with partners, and ensure successful data platform adoption and repeatable delivery practices while spending significant time on customer sites.

Lead and grow an analytics engineering team to build a trusted semantic metrics layer, scalable dimensional models, and governance. Partner cross-functionally to deliver reliable data products, improve pipelines and observability, set technical standards, and enable self-service analytics, experimentation, and ML while balancing scalability and business impact.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Own and build customer health, usage/adoption, and product configuration data models. Produce ad-hoc and recurring analyses to identify upsell/expansion opportunities, partner with CS, Sales, Product, and Data teams, and present actionable insights to leadership to drive revenue-relevant actions.

Lead end-to-end funnel analytics and optimization for SMB lending, identifying friction and bottlenecks, designing measurement frameworks, running experiments (A/B testing), and partnering with Risk, Operations, Product, Engineering, and AI teams to deploy automation and AI solutions that improve conversion, cycle time, and customer outcomes while managing risk.

Hands-on engineering role to design, build, and maintain scalable ETL/ELT data pipelines, data warehouses and lakes, and data models. Optimize batch and near-real-time processing, implement query optimization and data quality checks, support AI data workflows, and collaborate with architects, analysts, and stakeholders.

Lead Adobe Analytics architecture and MarTech ecosystem design, implement data layers and tagging across web and mobile, ensure QA and privacy compliance, enable reporting and audience activation, and drive cross-functional measurement and governance for personalization and optimization.

Design and implement a scalable Elasticsearch-based analytics platform integrated with an Oracle data warehouse. Architect data models, ingestion/CDC pipelines, index/shard strategies, and monitoring. Optimize cluster, queries, and caching for sub-second dashboard performance, perform load testing and capacity planning, and produce operational documentation and SLAs.

Lead development of scalable marketing data models, pipelines, and BI solutions. Partner with Marketing to define metrics, build dashboards, enable self-service analytics, and drive data governance and best practices.

Lead measurement strategy for paid and performance marketing, design and interpret A/B and lift tests, run incrementality and attribution analyses, and optimize channel budgets. Build business cases, develop dashboards and BI workflows, evaluate AI-enabled analytics tooling, and enable self-serve analytics. Partner cross-functionally and present insights to leadership to drive experimentation, growth, and LTV outcomes.

The Senior Director will establish and lead the Real-World Data & Analytics group, oversee RWD strategy, engage in complex analytics projects, and build a high-performing team in the oncology domain.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights; manage people, mentor staff, partner with product and engineering, and build accessible data products and measurement practices.

The Senior Data Scientist will lead revenue-driving initiatives, optimize strategies, enhance data analysis techniques, and improve data pipelines for maximum revenue impact.

Lead a team of analysts to advance fraud and safety operations through analytics, ensuring robust data products and compliance while empowering stakeholders with actionable insights.

Lead product analytics: build and maintain dbt models and Looker dashboards, define KPIs, analyze funnel and user journeys, design and evaluate A/B tests, size roadmap impact, and deliver partner and ad-hoc insights to inform product and executive decisions.

Lead and develop a team of partnership analysts to evaluate, optimize, and scale partner relationships. Design experiments, forecasting and ROI models, build reporting/dashboards, run cohort/funnel/retention analyses, own testing frameworks, and provide data-driven recommendations to cross-functional partners.

Lead and own the population health analytics pipeline: intake and reconciliation of claims, eligibility, and MAO-004 data; identify and reconcile care gaps and closures; deliver practice-level performance analysis and billing reconciliations; build funnel instrumentation; document, standardize, and automate pipelines with Product and Engineering. Ensure billing-grade accuracy and support program measurement aligned to CMS reconciliation windows.