Top Remote Data & Analytics Jobs in Tampa, FL

Build and maintain commercial data pipelines, transformations, models, integrations, and data products in Snowflake. Responsibilities include data modeling, quality validation, monitoring, troubleshooting, backfills, operational automation, documentation, and stakeholder collaboration. The role supports analytics, reporting, Streamlit, and AI-enabled use cases while maintaining reliable production workloads, privacy controls, and engineering standards.

The Data Steward maintains accurate, compliant, and standardized master and reference data across enterprise systems. Responsibilities include enforcing governance policies, validating and remediating Salesforce records, auditing and cleansing data, resolving data issues, supporting migrations and integrations, maintaining data dictionaries, and creating reports and dashboards. The role collaborates with global business, operations, sales, technology, and governance teams to improve data quality, support compliance, promote user adoption, and enable reliable reporting and decision-making.

Owns governance, quality, standards, and lifecycle management for eight master data domains across ERP and related systems. Administers NetSuite master data, defines validation and error-proofing controls, resolves data discrepancies, maintains audit-ready documentation, and reports quality KPIs. Partners with IT, Supply Chain, Finance, Commercial, Regulatory, Customer Care, and other teams on integrations, migrations, product launches, compliance, serialization, and pricing. Provides cross-functional guidance and drives data discipline without direct authority.

Leads competitive intelligence and market analysis for Medicaid, DSNP, and Marketplace RFPs. Reviews competitor responses, identifies gaps and differentiators, develops recommendations, maintains intelligence databases, supports capture strategy and oral presentations, and advises business development, product, legal, and executive stakeholders. Provides benchmarking, proposal analytics, training, and protest support while refining RFP methodologies. Requires 50% or more travel.

Leads enterprise data, analytics, business intelligence, and AI strategy across healthcare payer functions. Partners with executives to prioritize analytics initiatives, build reporting and predictive insight capabilities, establish data governance and accountability, and drive measurable business outcomes. Oversees cross-functional teams, enterprise application development, Azure architecture, quality automation, DevOps, and intelligent automation while engaging C-suite and board stakeholders.

Analyze performance marketing and subscription-funnel data, including acquisition efficiency, conversion, retention, churn, and customer lifetime value. Build automated Domo dashboards and governed reporting pipelines from multiple data sources. Investigate data anomalies, analyze A/B tests, define KPIs, and communicate insights to executives. Partner with marketing, product, engineering, finance, agencies, and BI contractors while independently executing analytics projects and improving reporting workflows.

Design and maintain large-scale ETL/ELT data pipelines using Python, Airflow, Spark, and Flink. Process and transform massive datasets, develop data models for analytics and dashboards, automate workflows in Unix/Linux environments, and debug distributed systems. Collaborate with cross-functional teams to ensure data accuracy, reliability, scalability, and availability across Akamai’s global network.

Builds and manages clinical outcomes and client experience measurement programs. Responsibilities include administering surveys, consolidating data, defining measurement methodologies, developing scorecards and recurring reports, analyzing trends, and connecting outcomes to provider network performance. The role translates complex findings into actionable recommendations for clinical and operational leaders, supports quality improvement initiatives, and contributes to research projects, white papers, and thought leadership.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Conducts operations research and advanced analytics to optimize public-sector command performance and reduce costs. Develops optimization, statistical, simulation, regression, mathematical, and decision-analysis models; implements analytical models in Python; performs data analysis; supports software development; assesses operational questions; and prepares decision briefings, reports, presentations, and recommendations for senior leadership.

Collects and analyzes performance data, identifies trends, evaluates program effectiveness, and develops reports and visualizations for stakeholders. The role standardizes datasets, improves data collection and analytical methods, and supports data-driven decisions. It requires statistical analysis, data manipulation, visualization, and familiarity with machine learning and predictive analytics. The position is contingent on contract award and requires the ability to obtain and maintain an active Secret Clearance.

Reviews and evaluates domain-specific documents, providing structured feedback on quality, accuracy, and relevance. The role requires strong analytical and written communication skills, detailed document review, proficiency with spreadsheet and presentation software, and the ability to follow structured guidelines. Candidates must have a bachelor’s degree, at least three years of relevant professional experience, English proficiency, and reside in the United States, Europe, the United Kingdom, or Canada.

Develop and evaluate realistic Excel tasks and solutions for AI training data. Apply advanced Excel capabilities including formulas, PivotTables, data modeling, dashboards, Power Query, Power Pivot, and VBA across multiple industries and business functions. Provide written feedback, close research knowledge gaps, improve model performance, and collaborate with subject matter experts. Requires reliable weekday availability, initially 40 hours per week and 20 hours thereafter.

Review and assess domain-specific documents, provide structured feedback, and evaluate quality, accuracy, and relevance. The role requires strong analytical, written communication, document review, and attention-to-detail skills, along with proficiency in Excel, PowerPoint, and Word. Candidates must have a bachelor’s degree, at least two years of relevant professional experience, and be based in the United States, Europe, the UK, or Canada.