Top Senior Data & Analytics Jobs in Boston, MA

The Senior Platform Engineer will support Workday functional configurations, improve processes, and provide troubleshooting and documentation for HR technology solutions.

The Manager of Media Analytics & Optimization will lead media performance measurement, drive insights for decision-making, and foster collaboration with senior stakeholders, while utilizing skills in analytics and AI.

As a Product Analyst, you will analyze customer behavior and product performance, create dashboards, and support decision-making through data insights and metrics definitions, while collaborating across teams.

The Director of Marketing Analytics leads a team of analysts, drives marketing strategy through data insights, oversees measurement and experimentation, and fosters cross-functional collaboration.

Lead statistical programmer responsible for developing SDTM and ADaM datasets, producing TLGs, creating reusable SAS macros, validating outputs, configuring CDA in elluminate, mentoring programmers, and ensuring regulatory and quality compliance for clinical trial reporting.

Lead the People Analytics team to develop data tools for decision making, manage data governance, and collaborate with diverse teams for effective people data usage.

The Staff Data Engineer will build and manage a data lake, optimize data pipelines, collaborate with teams, and support AI projects while ensuring quality data solutions.

The role involves leading teams to develop AI solutions addressing sustainability challenges, managing client accounts, and upholding ethical standards in technology integration.

The Senior Business Intelligence Engineer will design, develop, and optimize BI dashboards and reports using Amazon QuickSight, engaging with stakeholders and mentoring junior team members.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.