Top Hybrid Senior Level Data & Analytics Jobs in Dallas-Fort Worth, TX

The Senior Analytics Consultant will analyze complex business challenges, perform data analysis, lead projects, and mentor junior members within the Incentive Compensation Center of Excellence team.

The role involves leading customer data strategy and governance, ensuring data quality and governance, and modernizing data platforms. Responsibilities include executing BSA/AML data strategy and collaborating across teams to enhance data insights and compliance.

The Sr. Associate will provide valuation support, manage valuation models, and produce property performance reports for portfolio companies and Blackstone.

The Director of Data Analysis will lead the Small Business Bank Data Analysis team, develop data management strategies, oversee data quality, and manage a high-performing team, while collaborating with various departments on data needs.

This role leads marketing analytics supporting strategy through insights, A/B testing, dashboard creation, and martech integration.

As a Senior Data Architect, you will design and optimize complex data warehouses, analyze BI data for growth, and ensure data quality and integrity through collaboration with IT and business teams.

The Tax Technology Manager optimizes tax processes via governance and design of financial systems, focusing on Vertex and SAP integration. Responsibilities include system design, collaboration with stakeholders, and governance of tax technology systems.

The Director of Credit Onboarding oversees the evaluation of new clearing member applicants, managing risks and ensuring compliance with rules, while leading a team in credit risk assessments, stakeholder communications, and process enhancements.

Lead the design and execution of data validation strategies during ERP implementations, drive impactful results, and manage stakeholder relationships to address data issues.

Lead data initiatives with hands-on machine learning expertise, develop and deploy models, analyze data for business opportunities, and communicate insights effectively.

Design, build, and maintain data pipelines while ensuring data quality and collaboration with data teams. Troubleshoot issues and improve performance.