Enterprise Risk Management Data Analytics Lead

OVERVIEW

The Company

U.S. Financial Technology (U.S. FinTech) is seeking an experienced Enterprise Risk Management Data Analytics Lead to join our team of talented professionals. This is a full-time remote opportunity.

U.S. FinTech built and operates the largest and most advanced mortgage securitization platform in the world, supporting the Uniform Mortgage-Backed Security (UMBS) of Fannie Mae and Freddie Mac.

Supporting 70% of the mortgage-backed securities in the market, U.S. FinTech provides best-in-class single-family issuance, bond administration, disclosure, and tax services. We support a broad portfolio of products for our clients with full lifecycle management.

Our market-leading, cloud-based, end-to-end platform executes transactions on an extraordinary scale which has bolstered liquidity in the secondary mortgage market, one of the largest and most important financial markets in the world. Our unique approach to securitization combines the best minds in financial services with the know-how, flexibility, and innovation of leading technologists.

RESPONSIBILITIES

Job Information This individual will work as part of the U.S. FinTech's Enterprise Risk Management (ERM) function to provide timely reporting across multiple Risk Programs which evaluate the risk and controls structures surrounding the Issuance and administration of GSE Mortgage-Backed Securities. They will be the ERM team’s primary technical resource for designing, developing, and executing data analytics-related activities for KRI, KI trending, graphing/visual display pan ERM. The role would utilize various technologies for the automation of reporting on Risk & Control Self Assessments, operational events, issues and related validations. Role would liaise with ERM management regarding the reporting of ERM data for governance forums.

Key Job Functions

• Design, develop, and maintain enterprise risk management dashboards, executive scorecards, KPI frameworks, and analytics solutions using Power BI and other business intelligence of AI platforms. • Partner with business stakeholders to define metrics, gather and validate requirements, refine business questions, and translate needs into scalable reporting and analytics solutions. • Analyze business performance, risk indicators, and operational trends to identify opportunities, emerging risks, recurring issues, and areas for improvement. • Deliver meaningful insights and recommendations that support strategic decision-making, operational effectiveness, and business performance objectives. • Automate, optimize, and enhance recurring reporting processes to improve efficiency, scalability, accuracy, timeliness, and user adoption. • Support the development and adoption of advanced analytics capabilities, including AI-enabled reporting, predictive insights, and intelligent automation for ERM AI use cases. • Ensure the integrity, accuracy, and reliability of reporting through data validation, reconciliation, testing, quality assurance, and documentation standards. • Communicate complex analytical findings clearly and effectively to executives, business leaders, and non-technical stakeholders. • Build strong partnerships across business, technology, risk, compliance, audit, and other cross-functional teams to drive reporting maturity and continuous improvement. • Advance reporting and analytics capabilities by promoting trusted data standards, process optimization, automation, and data-driven decision-making.