Top Retail Data & Analytics Jobs in Boston, MA

The role involves operating and improving AI-driven data quality pipelines, managing offshore teams, and ensuring data accuracy and reliability. Responsibilities include monitoring pipeline performance, refining rules, and collaborating across teams to enhance data operations.

The Analyst IV is responsible for delivering scalable, secure POS and Payments technology solutions, leading design and integration, and ensuring system performance along with troubleshooting support.

Lead end-to-end analytics for Veterinary Diet, Science Diet, and Health & Wellness businesses. Build self-service dashboards, define KPIs, run deep-dive analyses, partner with technical and category teams, and deliver insights that improve customer experience and financial P&L.

The Ecommerce Analyst drives analytics and insights for eCommerce growth, focusing on merchandising and marketing channel performance. Key responsibilities include analyzing revenue drivers, building data-driven business cases, and collaborating cross-functionally to enhance decision-making processes.

The Product Analyst will analyze user behavior, define KPIs, lead A/B tests, and develop dashboards to improve eCommerce performance, collaborating with cross-functional teams globally.

The Senior Business Analyst will lead end-to-end process discovery and define workflows utilizing AI and automation to improve operational efficiency.

The Data Scientist I supports data analytics and modeling for logistics, using statistical methods and programming skills to generate insights and improve decision-making.

The Data Engineer will modernize and stabilize the data platform, optimize ELT/ETL pipelines, ensure data quality, and collaborate on AI architecture.

The Manager BI Analytics – Tableau Lead is responsible for providing insights through data analysis, developing Tableau dashboards, and collaborating with various business stakeholders to enhance operational processes and communicate findings effectively.

Oversee design, build, and maintenance of data pipelines and architectures, ensuring data reliability and supporting analytics and reporting needs.