Top Data & Analytics Jobs

The Business Analyst will provide operational and strategic analytical support to various business units, including updating financial models, interpreting data for insights, preparing reports, and leading the automation of complex datasets into actionable business insights.

As a Senior Data Analyst, you'll lead client communications on campaign strategies, derive actionable insights from data, and optimize marketing performance. You'll develop measurement tools and engage with clients to address their business challenges, ensuring effective campaign execution and reporting.

The Principal Data Analyst will manage and improve client advertising campaigns by developing strong relationships, coordinating project timelines, conducting performance analysis, and advising on new strategies. Responsibilities include overseeing campaign execution, documentation, and communication with clients, while also working with internal teams to optimize campaign effectiveness.

The Business Excellence Analyst collects and analyzes data related to business operations, ensures data accuracy, and supports continuous improvement initiatives. Responsibilities include preparing performance reports, conducting quality audits, identifying process improvements, and developing training materials.

The Business Systems Analyst is responsible for analyzing and developing marketing platform solutions, acting as a liaison between stakeholders and technical teams. The role involves gathering requirements, creating functional specifications, conducting gap analyses, and ensuring the alignment of technical solutions with business needs.

As a Data Scientist at Zeta Global, you will work on ETL processes, machine learning modeling, and marketing automation. Your responsibilities include designing and maintaining data pipelines, generating marketing reports, and ensuring data integrity, all while using advanced machine learning techniques in a fast-paced environment.

The Machine Learning Engineer will develop and deploy machine learning models, collaborate with cross-functional teams, and enhance data-driven decision-making within the company. Responsibilities include utilizing AWS services, containerization technologies, and managing workflows to create production-ready ML systems.