Top Fintech Data & Analytics Jobs

The Senior DataOps Engineer oversees data management and storage systems, ensuring timely access to secure and accurate data, improving data workflow automation, and collaborating with teams to meet business needs.

Lead analytics efforts by designing, validating, and deploying queries and reports, building visualizations, automating data processes, partnering with stakeholders including C-suite, documenting processes, performing root-cause analysis, and supporting projects across business, operations, and risk. Responsible for data warehousing practices, SQL/Python work, BI tool administration, and delivering insights to drive decision-making.

The CX Automation Performance Analyst manages post-launch AI programs, ensuring ongoing performance and optimization, building dashboards, and maintaining documentation.

As a Senior Data Engineer, you will build and maintain data pipelines, support analytics needs, and ensure data integrity for operations and reporting at Finix.

As a Senior Analytics Engineer, you'll transform complex data into reliable products using SQL and cloud-based warehouses, ensuring data quality and supporting analytics across the organization.

As a Staff Data Engineer at DAT, you will partner with finance teams to build automated reporting systems, data models, and visualizations. You will ensure data accuracy and contribute to financial workflows and reporting processes with accountability and collaboration.

The PM Engagement Analyst supports the senior PM Engagement team by enhancing research workflows, analyzing portfolio performance, and leveraging data analytics using Python and SQL.

As a Senior Quantitative Researcher, you will analyze large data sets, build statistical models, implement trading strategies, and develop quantitative research tools.

As a Credit Risk Senior Analyst at Marqeta, you'll lead underwriting strategies, refine credit policies, conduct risk analyses, and present findings to senior management.

The Staff Data Analyst will enhance data usage for strategic decisions, architect scalable models, partner across teams on data solutions, and lead analytics engineering standards.