Top Data & Analytics Jobs in Austin, TX

The Market Risk Analyst will monitor SBL lines of credit, assess market risks, manage collateral, develop risk models, and prepare reports.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

The Financial Systems Analyst manages NetSuite, optimizes business system performance, supports users, ensures data integrity, and collaborates on process improvements.

The Senior Product Analyst at Toast collaborates with various teams to analyze data, develop measurement frameworks, and enhance product development through insights, dashboards, and reporting tools.

The CX Analytics Engineer at Coinbase will design, build, and maintain data pipelines and models for customer experience and compliance using SQL and modern data tools.

The Pricing Associate will provide pricing guidance for clients, conduct financial analysis, improve pricing models, and support decision-making.

Lead Pager Health’s enterprise data and reporting strategy, build a centralized data and reporting shared services function, own internal dashboards and client-facing analytics, partner with Product and Engineering on data architecture and governance, mentor data teams, prioritize and deliver data initiatives, and drive continuous improvement in tooling, automation, and data storytelling to support growth, efficiency, and client outcomes.

Lead a unified analytics organization for Marketing and Product, define shared metrics and measurement frameworks, deliver executive-ready insights, build forecasting and experimentation programs, partner with engineering and privacy teams, and hire and mentor multi-layer analytics teams to drive product adoption and business outcomes.

Design, develop, and maintain forecasting and optimization models for contact forecasting, headcount planning, staffing and budget. Partner cross-functionally to produce data-driven recommendations, present to leadership, and mentor forecasting analysts.

Lead end-to-end data science initiatives: design, deploy, and monitor production ML models for credit risk, pricing, collections, and fraud. Partner cross-functionally to integrate models, set development standards, mentor team members, and maintain reliable, scalable machine learning pipelines and monitoring systems.