Top Artificial Intelligence Data & Analytics Jobs in Austin, TX

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

As a Principal Data Analyst, you'll lead credit analytics efforts, develop forecasting models, and collaborate with multiple teams to enhance Upstart's credit platform.

The Data Platform Engineer II role involves automating data infrastructure, scaling analytics platforms, and ensuring system reliability and security. Key responsibilities include managing CI/CD pipelines, configuring secure networking, and collaborating with Data & Analytics teams to optimize performance.

Responsible for managing all data management activities for clinical studies, including data collection, cleaning, reporting, and validation, while ensuring regulatory compliance and quality data delivery.

As a Digital Innovation Co-Op, you'll work on projects involving AI and machine learning to enhance supply chain operations, collaborating with engineers and data scientists to automate workflows and analyze data.

Analyze auction data to identify performance drivers and risks, collaborate with commercial teams, and provide actionable insights to optimize DSP outcomes.

Lead client-facing data solutioning and pre-sales efforts for Consumer verticals, design executable data architectures, support pursuit to close, and provide ~50% hands-on delivery and architectural oversight while ensuring information security and data privacy compliance.

Lead analytics implementations using Google Analytics and Tag Manager for clients, providing mentorship and managing projects with a focus on enhancing clients' digital strategies.

The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & Insights.

The Solutions Architect leads client integration of Cedar's platform, ensuring successful project delivery through client communication and technical expertise while managing complex data structures and operational workflows.