Enterprise Risk Management Data Analytics Lead

U.S. Financial Technology•Remote,

2d•$156,500 - $181,000•Remote

About The Position

U.S. Financial Technology is seeking an experienced Enterprise Risk Management Data Analytics Lead to join its Enterprise Risk Management function. This full-time remote role provides timely reporting across multiple risk programs that evaluate risk and control structures surrounding the issuance and administration of GSE mortgage-backed securities. The role is the ERM team’s primary technical resource for designing, developing, and executing analytics activities, including key risk indicator and key indicator trending and visual displays. It uses technology to automate reporting on risk and control self-assessments, operational events, issues, and related validations, and partners with ERM management on reporting for governance forums. The Lead develops dashboards, executive scorecards, KPI frameworks, and analytics solutions; works with stakeholders to define metrics and requirements; analyzes performance, risk indicators, and operational trends; and delivers insights to support strategic decisions and operational effectiveness. The role also advances reporting automation and AI-enabled analytics, safeguards data and reporting quality, communicates findings to executives and other stakeholders, and collaborates across business, technology, risk, compliance, audit, and other teams. U.S. FinTech operates a cloud-based mortgage securitization platform supporting the Uniform Mortgage-Backed Security of Fannie Mae and Freddie Mac. The company’s services include single-family issuance, bond administration, disclosure, and tax services.

Requirements

Bachelor’s degree in Analytics, Business, Data Science, Statistics, Mathematics, Finance, Computer Science, Engineering, or a related quantitative discipline.
Minimum of 7–8 years of management experience in enterprise risk or operational risk management.
Advanced proficiency in Power BI, including data modeling, DAX, Power Query, dashboard architecture, performance optimization, and executive reporting.
Strong hands-on experience with Python, SQL, and PostgreSQL, including data extraction, transformation, automation, analytical modeling, and reporting solutions.
Expertise designing, developing, and maintaining enterprise-scale dashboards, executive scorecards, KPI frameworks, and business intelligence solutions.
Advanced analytical and quantitative skills, including the ability to transform complex datasets into actionable insights and recommendations.
Experience partnering with senior stakeholders to turn complex business challenges into scalable analytical and reporting solutions.
Ability to analyze business performance, identify trends, risks, and opportunities, and influence strategic and operational decisions through data-driven recommendations.
Strong communication, presentation, stakeholder management, and consultative influencing skills across organizational levels.
Ability to operate independently in a highly visible individual-contributor role while leading initiatives and influencing outcomes across teams.
Experience delivering measurable business value through reporting innovation, process optimization, automation, and analytics-driven improvements.
Experience ensuring data integrity, governance, and reporting accuracy through validation, reconciliation, testing, quality assurance, and documentation.
Applicants must be authorized to work in the United States without requiring employer sponsorship now or in the future; H-1B sponsorship is not offered.
Successful applicants must complete a background investigation; this may include a credit check for positions in some business areas.

Nice To Haves

An advanced degree is preferred.
CISA certification is preferred.
AWS Certified Data Analytics, IBM Data Analyst Professional, or Google Data Analytics Professional certifications are a plus.
Experience with advanced analytics, predictive modeling, AI-enabled reporting, machine learning, or intelligent automation.
Experience in risk management, enterprise risk, compliance, audit, third-party risk, fintech, financial services, or another highly regulated environment is strongly preferred.
Familiarity with mortgage or securitization market processes is a plus.

Responsibilities

Design, develop, and maintain enterprise risk management dashboards, executive scorecards, KPI frameworks, and analytics solutions using Power BI and other business intelligence or 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 insights and recommendations to 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 advanced analytics capabilities, including AI-enabled reporting, predictive insights, and intelligent automation for ERM use cases.
Ensure reporting integrity, accuracy, and reliability through data validation, reconciliation, testing, quality assurance, and documentation.
Communicate analytical findings to executives, business leaders, and non-technical stakeholders.
Build partnerships across business, technology, risk, compliance, audit, and other cross-functional teams to improve reporting maturity.
Promote trusted data standards, process optimization, automation, and data-driven decision-making.
Provide timely reporting across multiple risk programs and support reporting of ERM data for governance forums.
Design, develop, and execute analytics activities for key risk indicator and key indicator trending and visual displays.
Automate reporting on risk and control self-assessments, operational events, issues, and related validations.