Top Senior Level Data & Analytics Jobs in Austin, TX

As a Senior Analytics Engineer II, you will transform raw data into structured datasets, manage data ingestion workflows, improve data pipelines, orchestrate workflows, ensure data accuracy, and collaborate with governance teams to maintain compliance.

The Senior Data Scientist will focus on analyzing and providing insights into Babylist's fulfillment and operations, particularly within the supply chain. This role involves collaborating with multiple teams to improve processes and data-driven decision making, with a strong emphasis on reporting and predictive modeling.

The Senior Research Analyst gathers and analyzes data from various sources to provide insights on market trends affecting the freight industry. They create reports and visual content to support business stakeholders, monitor freight market conditions, and contribute to thought leadership initiatives.

The Staff Data Scientist for Marketing at Realtor.com will analyze consumer behavior and engagement, create full funnel reporting, collaborate with marketing and engineering teams to establish best practices for performance media, and automate reporting for cross-functional teams while managing campaign budgets and optimizations.

The Senior Systems Administrator at St. Edward's University will provide technical support for enterprise systems, databases, and middleware applications. Responsibilities include application administration, software upgrades, maintaining application architecture, supporting integrations, and conducting system analysis, testing, and troubleshooting.

As a Senior Credit Resolution Ops Analyst, you will manage credit disputes, conduct investigations, and analyze account histories. You'll provide insights to mitigate risks and ensure compliance while enhancing servicing operations. Day-to-day tasks include processing high-risk customer requests, managing credit bureau reporting, supporting audits, and monitoring operational metrics.

The Senior Data Engineer will design and implement ETL processes and monitoring solutions, document datasets for data warehouse users, and provide technical support, primarily to the Data Science team. They will also collaborate with other departments to translate business needs into development tasks.