Top Hybrid Data & Analytics Jobs in Boston, MA

As an Analyst I on the Casino Product Analytics team, you'll analyze data to drive product strategy, evaluate performance, and guide product development through insights and recommendations.

As a Data Office Manager, manage data strategy in the healthcare landscape, collaborate with teams and stakeholders, and oversee project management while leading a diverse team.

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

Lead data science projects to optimize drug development using AI. Develop models for patient selection and clinical trial evaluations while collaborating with cross-functional teams to drive insights.

The Business Analytics Manager will partner with Lifecycle Marketing to enhance member communications, drive engagement, and inform strategic decisions using data analysis and insights.

As a Business Analyst, you will drive process optimization by collaborating with teams, analyzing current operations, and implementing innovative solutions using AI and automation tools.

The Solutions Engineer, Data role involves developing data solutions aligned with business goals, improving data quality, and leading technology strategies while collaborating with various teams.

This role involves leading data architecture strategies, collaborating with stakeholders, and implementing advanced data technologies to drive business growth at PwC.

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.

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.

The Senior Data Engineer will develop data governance frameworks, ensure data quality, manage tools for metadata and lineage, and collaborate with teams for data policies and training.