Top Senior Level Data & Analytics Jobs in Washington DC,

The Manager, Data & Analytics is responsible for overseeing measurement, insights, and performance optimization for media planning. This role involves developing measurement plans, managing dashboards and competitive intelligence, and conducting brand health surveys.

The SAS Analyst/Developer will develop and maintain SAS programs, leverage Python for data workflows, and collaborate with teams to translate business requirements into analytical solutions. Responsibilities include data validation, cleansing, optimizing processes, and documenting methodologies.

The role involves developing and implementing a strategic roadmap for marketing analytics, defining marketing attribution goals, analyzing complex data sets, and providing insights to optimize marketing strategies. The position requires collaboration across teams and thought leadership on marketplace trends.

As a Senior Data Engineer (AI), you will design and maintain data pipelines, manage infrastructure, and integrate AI/ML applications. This role involves collaboration across teams to enhance data-driven decision-making and cybersecurity solutions.

The Lead ETL Tester will design and execute test plans for data engineering projects, develop automated testing scripts using SQL/Python, validate data accuracy and consistency, and collaborate with teams to ensure quality in data engineering solutions. Responsibilities include conducting various types of testing, mentoring junior analysts, and staying updated with industry trends.

The Senior Staff AI Scientist will collaborate with subject matter experts to develop AI solutions, oversee data management, and mentor Data Scientists. Responsibilities include designing and deploying advanced AI solutions, ensuring high-quality data access, and fostering a culture of continuous learning within the team.

The Data Architect will design and optimize the organization's data infrastructure to align with business goals and enhance data-driven decision-making. Responsibilities include developing data solutions using various Azure services, managing data architecture, ensuring compliance with regulations, and collaborating with cross-functional teams to meet data infrastructure needs.