Top Senior Data & Analytics Jobs in Madison, WI

Own the enterprise data glossary, business definitions, governance policies, quality controls, lineage documentation, and approved sources of truth. Translate cross-functional data needs into reusable definitions and reporting, support business users, investigate data quality issues, and coordinate with product and technical teams on data model changes. The role operates independently as a senior individual contributor and drives adoption of governed data across internal and external stakeholders.

Lead Voice of Customer practice through survey and listening-program design, fielding, vendor coordination, data-quality oversight, and synthesis. Manage enterprise insights repositories, decisions journals, methodology libraries, and knowledge-transfer rituals. Maintain VoC and knowledge-management platforms, establish taxonomy and metadata standards, coach peers on research quality and documentation, and ensure organizational insights remain discoverable, credible, and reusable across staff transitions.

Designs and implements Google Cloud database migration strategies, including architecture, data models, database objects, pipelines, orchestration, security, and data transfers. Advises customers on Cloud Spanner and Cloud SQL implementations, translates SQL and stored procedures, configures Google Cloud components, performs performance testing, resolves performance issues, and delivers technical workshops and architectural recommendations.

Develop and optimize marketing reports, monitor product and advertising campaign KPIs, integrate and visualize data, investigate performance deviations, analyze campaigns, and recommend improvements. The role requires strong Google Sheets skills, basic SQL, A/B testing, mathematical statistics, and English proficiency. Python, web analytics, Google Ads, and BI experience are preferred. This is a fully remote position.

Leads supply chain analytics, reporting, automation, and Power BI solutions while managing product readiness portfolios for launches and product changes. Coordinates cross-functional deliverables, governance forums, SKU readiness, risk escalation, documentation, and milestone tracking across commercialization projects. Translates business needs into scalable analytics and digital solutions, communicates insights, and drives stakeholder adoption and operational improvements.

Leads the design and implementation of AI-powered data pipelines, enterprise feature stores, analytics-ready repositories, and self-service data access layers. Builds automated feature engineering, data quality, observability, and governance capabilities for large-scale data science workloads. Partners with Enterprise IT, establishes data availability and quality SLAs, integrates structured and unstructured data sources, and leads teams delivering scalable analytics infrastructure.

Reviews AI-generated documents, spreadsheets, and slide decks for accuracy, rigor, presentation quality, and domain-specific compliance. Evaluates outputs using quality rubrics, identifies factual and aesthetic errors, and provides structured written feedback. The role requires deep expertise in data quality and CRM operations, strong English fluency, and proficiency with Microsoft Office and Google Workspace. It is a fully remote, flexible independent-contractor engagement.

Analyzes, cleanses, validates, and prepares operational datasets for mailing, email, reporting, billing, and processing activities. Develops Databricks queries and Alteryx workflows to automate processes and improve data quality. Performs audits, reconciliations, root-cause analysis, and corrective actions while maintaining governance and security compliance. Provides actionable insights, mentors junior analysts, communicates findings, and leads continuous improvement initiatives.

Own Kepler’s transaction data feed end-to-end, ensuring accuracy, improving methodologies, developing QA frameworks, solving complex analytical problems, and prototyping enhancements. Analyze massive datasets, automate workflows with AI, evaluate client-facing AI outputs, address high-complexity customer questions, and collaborate with Research, Product, Data Science, and Engineering teams.

Leads analytics for SEO, AI search, website experience, CRO, and the organic enrollment funnel. Diagnoses performance across traffic, visibility, conversions, leads, applications, and enrollments; designs measurement approaches; reconciles web, search, CRM, and platform data; defines KPI and reporting requirements; and translates findings into executive recommendations. Partners with analytics and engineering teams to build scalable Databricks-based reporting and improve measurement of organic and AEO initiatives.