Top Data & Analytics Jobs in Austin, TX

The Overwatch Research Intern will support cybersecurity research, contribute to a machine learning project, and participate in team activities while developing technical skills.

As a Senior Associate, you will develop and implement IBM MDM solutions, mentor junior team members, and manage data quality frameworks while providing insights from data analysis.

As an SEO Analyst, you will analyze data to improve SEO strategies, provide performance reports, and collaborate with teams to enhance user experiences and brand visibility.

Analyze user behavior data to identify friction points, recommend changes for conversion optimization, and collaborate with teams to improve user flows through data-driven insights.

Lead the SEO team at Atlassian, focusing on B2B SEO strategy, mentoring, analytics, and cross-functional collaboration to enhance organic search performance.

The Senior Analyst, Fraud Investigations will identify and analyze fraud patterns, conduct investigations, and develop strategies to mitigate losses. They will leverage SQL and Snowflake to work with complex datasets and collaborate with multiple teams to enhance fraud detection frameworks.

The Data Analyst will analyze large datasets, develop reports, and collaborate with various teams to improve player engagement and experience.

This role involves collaborating to improve game metrics, analyzing player behavior, designing ETL pipelines, and ensuring data integrity to enhance user experience.

The Analytics Analyst I will design and develop Tableau dashboards, collaborate with teams for insights, communicate findings, and support analytics documentation and improvement.

The Data Analyst will partner with business stakeholders to conduct analytics projects, analyze large datasets, build reports, and generate insights to drive revenue operations at Realtor.com.

The Senior Analytics Engineer will build and scale the analytics foundation, transforming data for decision-making across multiple teams and ensuring data quality and automation.

Design and build secure data pipelines, lead data architecture, collaborate across teams, ensure data quality, and mentor other engineers.