Top Fintech Data & Analytics Jobs

Analyze check fraud chargebacks, charge-offs, and Reg E disputes using VISA Data Manager and related systems. Produce reports, requirements, process documentation, and analytical write-ups to identify trends and recommend solutions for fraud reduction.

As a Senior Data Engineer, you will build and optimize foundational datasets, data pipelines, and analytical dashboards while ensuring data quality management.

The Analytics Engineer will design, build, and maintain scalable data models, collaborating with various teams to ensure data quality and robust reporting, mainly using dbt and SQL.

The Credit Risk Analyst will analyze data to optimize credit risk and funnel conversion, utilize statistical tools for business strategy development, forecast delinquency, report on portfolio performance, and collaborate with cross-functional teams.

Lead data science projects at Parafin to leverage data for small business growth, focusing on portfolio monitoring, servicing, and infrastructure development.

The Market Risk Analyst supports risk oversight and portfolio management by analyzing exposures, developing risk tools, and monitoring performance across asset classes.

As a Data Engineer at Promise, you'll design data architectures, automate workflows, enforce data quality, and support analytics, enabling data-driven decisions.

The Senior Data Analyst will manage data quality and governance for regulatory compliance, build data marts, and optimize data models for performance and scalability. This role includes supporting regulatory exams, establishing monitoring for data feeds, and translating regulatory requirements into data flows.

As a Data Engineer, you will build and own the data infrastructure, design pipelines, ensure data quality, and implement DataOps practices while collaborating closely with product and engineering teams.

Build reliable data models and semantic layer for AI-powered analyses. Support Product, Finance, and Customer Success with SQL-based analytics, BI dashboards, and stakeholder storytelling. Standardize data team processes, prioritize work, and collaborate across company to enable data-informed decisions.