Top Fintech Data & Analytics Jobs in Boston, MA

Lead architect for Compliance data at Coinbase, defining data governance frameworks, designing data contracts, mapping data lineage, and quantifying data impact to enhance compliance reporting and data quality processes.

As a Data Engineer, you'll design data models, build data pipelines, implement AI capabilities, and ensure data quality for analytics. You'll collaborate with stakeholders to deliver robust datasets and support cross-functional strategies using advanced data tools.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

As the Capital Markets Manager, you will secure funding through securitization programs, manage partnerships, and lead structured finance negotiations while mentoring your team.

The Senior Analytics Engineer will enhance data models, optimize performance in Snowflake, and bridge data engineering with analytics teams for strategic decision-making.

The analyst will support portfolio reporting, analysis, and credit monitoring, while assisting senior team members and producing performance reports.

The Risk Analyst will develop strategies to mitigate fraud risk, analyze data, and collaborate with various teams to support low friction customer experiences. Responsibilities include reviewing accounts, creating analytical models, and reporting on progress against business goals.

The Analyst II role focuses on leveraging data analytics to optimize credit strategies, conduct portfolio analysis, and develop credit risk capabilities while collaborating across various teams.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Support sales intelligence by collecting, preparing, and analyzing sales and marketing data; maintain dashboards and data quality; run pipeline and win/loss analyses; translate findings into clear visualizations and reports for stakeholders.