Top Data & Analytics Jobs in Boston, MA

Lead commercial analytics to diagnose sell-through, pricing, promotions, assortment, and retailer execution. Build causal measurement, test-and-learn designs, elasticity and incrementality analyses, and deliver executive-ready recommendations to optimize revenue, margin, and share.

Partner with Lifecycle Marketing to analyze member communications, design and evaluate A/B tests, build dashboards, develop data models linking messaging to engagement and retention, and present actionable insights to improve lifecycle strategy.

The VP of Alternative Data Strategy drives sourcing, prioritisation, and implementation of alternative datasets, aligning data opportunities with investment strategies and governing data usage across teams.

Lead RevOps data modeling, ETL/DBT development, and dashboarding to ensure high-quality revenue data. Build Snowflake data marts, author complex SQL, create Tableau visualizations, apply AI/ML forecasting, and partner with Sales, Marketing, Finance, and IT to resolve data quality and reporting issues.

As a Senior Analyst, you'll analyze customer behavior, evaluate promotional strategies, and provide data-driven insights to influence key business decisions at DraftKings.

The role involves developing statistical models and analyses to address client business issues, guiding decision-making with data insights and mentoring associates.

The Principal Front-Office Engineer will lead the design and implementation of AI-driven solutions in investment strategies, collaborating with analysts to enhance toolsets and reporting systems.

In this co-op role, you'll analyze qualitative and quantitative consumer data, assist in research plans, translate insights into product recommendations, and collaborate cross-functionally to support product and marketing strategies.

Support Commercial and Supply Chain with analytics and reporting: design and automate reports, build dashboards, perform complex correlation and predictive analyses, ensure data integrity across stakeholders, lead requirements and data flow design, and present actionable insights to leadership.

This role involves applying advanced data science and machine learning methods to healthcare data, leading teams, managing client relations, and developing analytics products for payers, while mentoring junior staff.