Top Senior Analytics Jobs in Austin, TX

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

Lead pricing analytics for merchant/platform deals and international market expansion. Define pricing strategy, run economic analyses, design and test pricing constructs, and collaborate with product, partnerships, credit, finance, capital markets, and engineering to optimize portfolio performance.

Lead data analysis projects to help merchant partners understand Upside's impact, manage analytics relationships, and improve product strategy.

Lead strategic revenue cycle analyses to diagnose patient billing and collections performance, quantify ROI and value, build executive-ready recommendations and playbooks, partner cross-functionally, and mentor teammates to drive scalable, data-driven improvements.

The Senior Data Scientist will build frameworks for data-driven decision making, develop predictive models, ensure data quality, and enhance customer experiences through analytics and operational insights.

Leads the statewide campaign’s data and analytics strategy for GOTV. Oversees voter data, campaign systems, data standards, dashboards, reporting, targeting, modeling, and Election Day monitoring. Provides actionable analysis to leadership and organizing teams, coordinates with campaigns and partner organizations, manages complex data programs, trains staff, and ensures systems support fast, accurate decision-making during Early Vote and Election Day.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, experiments, and analyses; surface insights; make recommendations; and drive decisions and execution with cross-functional stakeholders. The role requires independently structuring ambiguous problems, interpreting data, communicating persuasively with leadership, and delivering measurable business impact.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Lead supply-and-demand forecasting for the psychiatry service line: build and maintain S&D models, integrate models into core data infrastructure, define operational metrics (capacity, clinician utilization, hiring targets), run forecast vs. actual audits, and partner cross-functionally to guide hiring, resource allocation, and operational improvements.

Analyzes healthcare claims, provider, reimbursement, and financial data to support out-of-network dispute negotiations, arbitration, QPA accuracy, and IDR performance. Builds SQL-based reports, dashboards, data processes, metrics, and financial views; validates data quality; integrates internal and external sources; identifies trends and risks; and presents actionable recommendations to leadership and cross-functional stakeholders.

The Senior Analyst will lead digital measurement analytics for emerging payments platforms, including data collection, validation, reporting, and feature performance measurement. Responsibilities include partnering with marketing, technology, digital, and analytics stakeholders; delivering accurate, compliant projects; communicating insights; supporting strategic priorities; and developing analytics roadmaps. The role requires hands-on problem solving, visualization, web analytics, and collaboration across Agile teams.

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.

Lead product analytics for Guest or Host App: analyze large datasets, design and evaluate experiments, build metrics and reporting tools, apply statistical and causal methods, partner cross-functionally, present insights to stakeholders, and leverage AI to automate tasks.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Lead current-year and long-term AP volume forecasting using statistical and AI/ML methods; diagnose supply-demand drivers; close analytic data gaps; translate analyses into strategic recommendations; mentor staff and communicate forecasts and risks to senior stakeholders across College Board.

Analyze and reconcile enrollment and member data across Medicaid, Medicare, Marketplace, and Duals. Build reports and dashboards, fix data issues, apply statistical techniques, consolidate disparate sources, and partner with operations to ensure accurate coverage and regulatory compliance.

Lead implementations and ongoing analytics consulting for community health centers: extract, clean, and analyze EHR data (heavy SQL), build reports and visualizations, manage projects and stakeholders, train client data teams, and inform product improvements based on customer feedback and domain expertise.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.