Top Hybrid Data & Analytics Jobs in Boston, MA

Monitor, analyze, and forecast KPI performance across direct digital and call center sales. Investigate trends, query large datasets, produce actionable insights and presentations, support financial planning, and partner with reporting and analytics teams to improve operational performance.

Lead enterprise healthcare data modeling: design and maintain conceptual/logical/physical models, integrate varied clinical sources, implement common data model transformations, monitor data quality, and collaborate with clinicians, data scientists, and engineers.

Define and lead enterprise data governance: create standards, operating model, and AI-ready data practices. Partner with data product managers, platform engineering, security, legal and privacy to enable self-service, metadata, lineage, quality, access controls, and compliance while building governance councils and driving adoption.

Lead data validation and risk analytics practice, set strategic direction, manage multiple client engagements, and drive business development. Use Alteryx and Python for data integration, build dashboards in Power BI/Tableau, apply predictive analytics and statistical modeling, ensure data integrity/security, mentor teams, and cultivate executive client relationships.

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

Design and maintain analytics frameworks, data architectures, and pipelines using SQL and cloud platforms. Build scalable dashboards and reports, support experiment design and analysis, validate data quality, automate reporting, and document technical designs. Collaborate cross-functionally to deliver data products and insights that measure digital asset impact and support business decisions.

Support Business Banking with analytics, reporting, dashboards, and automation to drive deposit acquisition, onboarding, funded balance growth, and retention. Produce forecasting and pipeline reporting, provide deposit strategy and profitability insights, enable go-to-market and campaign analysis, and standardize onboarding and data processes to improve efficiency and data quality.

Lead the strategy and execution of real-world data capabilities, focusing on data lifecycle management, vendor relationships, and collaboration with various teams to deliver analysis-ready datasets.

Lead a team to design and operate scalable Databricks/lakehouse platforms, ETL/ELT pipelines, data models, BI dashboards, and productionized ML. Ensure data quality, governance, and deliver actionable analytics and KPIs to drive business decisions while mentoring engineers, scientists, and analysts.

Build and productize externally consumable data assets from concept to delivery. Define schema, governance, SLAs, documentation, and delivery (Snowflake share, SFTP, API). Partner cross-functionally to productionalize datasets, monitor quality, iterate on customer feedback, and create repeatable productization frameworks.