Top Senior Data & Analytics Jobs in Boston, MA

The Director of Biostatistics leads a team in clinical research, developing statistical plans, collaborating across departments, and ensuring regulatory compliance.

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 Senior Data Engineer will architect AI infrastructure, design high-performance data systems, manage AI pipelines, and collaborate with cross-functional teams. Responsibilities include implementing data architecture best practices and providing documentation and leadership in data orchestration.

As a Senior Data Engineer, you'll design scalable data models, build automated ETL pipelines, and mentor junior engineers while collaborating across teams.

As a Lead Data Engineer, you will collaborate in Agile teams to design and implement financial data solutions, utilizing extensive programming and cloud technologies.

Lead the development of scalable data platforms and analytics systems, overseeing teams in building data pipelines, advanced algorithms, and dashboards for data-driven decision making.

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.

Design, build, and maintain scalable BI solutions and Power BI dashboards for CRM performance and lifecycle analytics. Integrate AEP, RTCDP, and CRM data, ensure data quality and governance, automate reporting across brands/markets, support attribution and migration to cloud, and collaborate with cross-functional teams to deliver actionable marketing insights.

Lead the marketplace analytics by optimizing monetization strategies, monitoring performance, creating dashboards, and analyzing supply-demand dynamics. Collaborate cross-functionally to drive engagement and profitability.

Oversee data ingestion and transformation, manage finance data sources, ensure scalability and reliability of data platforms, and collaborate with stakeholders to align data engineering with organizational goals.