Top Remote Data & Analytics Jobs in Houston, TX

As a Data Scientist in Customer Analytics, you will analyze customer data, measure Cresta's impact through experiments, and build dashboards for insights. You'll collaborate with cross-functional teams and support strategic customer initiatives.

The Workday Finance Business Analyst will configure and support Workday Financials, addressing user requests and leading system enhancements while collaborating with Finance stakeholders to drive strategic initiatives.

Assist in collecting, cleansing, and analyzing datasets to produce actionable insights, reports, and dashboards for informed business decisions.

Design, build, and own end-to-end data systems and pipelines powering payments, fraud response, and reporting. Implement streaming and batch integrations, APIs, and workflow orchestration. Define data correctness with monitoring, alerting, and tests. Create reusable patterns and collaborate with stakeholders to clarify requirements and tradeoffs.

As an Analytics Engineer, transform raw data into metrics, manage data pipelines, ensure data integrity, and collaborate with teams for analytics solutions.

The Data Architect will design scalable data models, transform raw data into actionable insights, and deploy analytics solutions for healthcare providers, with a strong emphasis on SQL proficiency and cloud technologies.

The Data Privacy Compliance Analyst will support the development and implementation of data privacy programs, assist privacy operations, and ensure compliance with global privacy laws.

As a Senior Data Analyst, you'll provide actionable insights by analyzing product and engineering data, partnering with leadership on metrics frameworks and decision support for product delivery.

The Data Analyst will maintain KPI standards for Customer Support, build dashboards, produce analyses, and lead metric alignment conversations, ensuring accurate data interpretation and decision-making support.

Build dashboards and reports tracking enrollment, attendance, engagement, and attrition. Develop predictive models to identify at-risk students, analyze withdrawal causes, monitor early-warning indicators, partner with cross-functional teams to design retention interventions, and present insights to leadership while supporting data pipeline accuracy.