Top Data & Analytics Jobs in Boston, MA

The Senior Pricing and Packaging Analyst will analyze data to inform pricing strategies, develop recommendations, and work collaboratively across teams to implement these strategies.

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.

As a Senior Data Engineer, you will manage data integration, optimize performance, mentor junior engineers, and collaborate with product teams on innovative solutions in healthcare data modeling.

The Manager of Ontology and Data Modeling develops and maintains enterprise ontologies, collaborates with teams across Capital One, and advocates for semantic technology integration in products and services.

Lead operational design and engineering for the data platform: own Snowflake and dbt administration, automate platform operations and CI/CD, monitor platform health and observability, enforce governance and access, optimize performance and costs, and develop AI/agent integrations to enable governed data access for business users.

Lead redesign of the Customer Success unified data model and AI data strategy. Build and optimize pipelines, integrations (contact center), testing/monitoring, and a documented semantic layer. Manage and mentor a small team, partner cross-functionally on KPIs, governance, and data quality, and ensure CS data is reliable for dashboards, reporting, and AI use cases.

As an Advisor Loan Consultant, you'll analyze advisor loan programs, produce detailed reports, interpret profitability, and develop key performance indicators.

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.

Lead data and software QA for enterprise data platforms: define testing strategy, build automated test frameworks, validate ETL/ELT and data transformations, run data quality checks and reconciliations, test APIs and data products, analyze datasets with SQL to find defects, drive root-cause resolution, participate in Agile ceremonies, and mentor team members to improve quality practices.

Lead Data Scientist responsible for guiding projects, mentoring a team, developing data-driven solutions, and collaborating across departments to drive insights.