Top Senior Data & Analytics Jobs in Boston, MA

The Manager of Advanced Analytics & Automation leads the strategic analytics and AI automation initiatives for customer intelligence, building data models, insights, and automation workflows to enhance customer success and retention.

Lead and grow an analytics engineering team to deliver scalable data models and reporting for Product, Marketing, Finance, and other stakeholders. Drive BI platform vision, collaborate with Product and Data Governance, prioritize work, implement agile practices, and ensure high data quality and performant transformations.

The Associate Director, Biostatistics is responsible for statistical guidance in clinical study design, data analysis, and regulatory submissions, leading clinical study teams to ensure timely and quality outcomes.

The Data Engineer III designs and optimizes data pipelines, supports data initiatives, ensures data quality, and collaborates across teams to develop BI solutions and documentation.

The Sr. Analytics Engineer at Philo is responsible for designing data models, governing business metrics, collaborating with stakeholders, and ensuring data quality and documentation for analytics purposes.

Manage the data architecture and strategic planning for the Sales team, optimizing processes through data and AI for targeting accounts and pricing strategies.

The Customer Value Manager drives ROI analysis, builds business cases, partners with teams, and ensures customer satisfaction throughout the lifecycle.

The Analytics Engagement Manager ensures client success with data adoption, manages analytics projects, gathers requirements, and develops Statements of Work while providing thought leadership in healthcare commercial intelligence.

The Principal Data Analyst will manage pricing and profitability strategy for Workhuman's E-commerce store, leveraging data analysis and cross-functional collaboration to drive decision-making and implement improvements in pricing strategies.

Seek a Lead Analytics Engineer to design and build scalable data solutions, oversee data engineering, and collaborate with cross-functional teams to meet data needs.