Accountabilities

The Enterprise Risk Management Data Analytics Lead will serve as the primary technical resource for analytics and reporting initiatives across multiple risk programs. They will help strengthen risk visibility, improve governance reporting, and promote data-driven decision-making. Key responsibilities include:

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 develop scalable reporting solutions.

Analyze business performance, key risk indicators, and operational trends to identify emerging risks, recurring issues, and improvement opportunities.

Deliver actionable insights and recommendations to support strategic decisions, operational effectiveness, and business performance objectives.

Automate and optimize recurring reporting processes to improve efficiency, scalability, accuracy, and timeliness.

Support the development and adoption of advanced analytics capabilities, including AI-enabled reporting, predictive insights, and intelligent automation for enterprise risk management use cases.

Ensure reporting integrity and reliability through data validation, reconciliation, testing, quality assurance, and documentation.

Communicate complex analytical findings clearly to executives, business leaders, and non-technical stakeholders.

Collaborate with business, technology, risk, compliance, audit, and other cross-functional teams to improve reporting capabilities.

Support reporting and governance activities related to Risk and Control Self-Assessments, operational events, issues, and associated validations.

Prepare and deliver risk reporting and analytics for enterprise governance forums.

Promote trusted data standards, process optimization, automation, and continuous improvement across the organization.

Requirements

The ideal candidate will combine substantial enterprise risk management experience with advanced technical expertise in data analytics, business intelligence, and reporting automation. They should be comfortable operating independently in a highly visible role while influencing stakeholders across the organization. Required qualifications include:

Bachelor's degree in Analytics, Business, Data Science, Statistics, Mathematics, Finance, Computer Science, Engineering, or a related quantitative discipline.

Advanced degree preferred.

At least 7–8 years of management experience in enterprise risk or operational risk management.

Proven experience designing and maintaining enterprise-scale dashboards, executive scorecards, KPI frameworks, and business intelligence solutions.

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 for data extraction, transformation, automation, analytical modeling, and reporting.

Advanced analytical and quantitative skills, with the ability to turn complex datasets into meaningful business insights.

Demonstrated experience translating business challenges into scalable analytics and reporting solutions in collaboration with senior stakeholders.

Strong ability to identify trends, risks, and opportunities and influence strategic and operational decisions through data-driven recommendations.

Excellent communication, presentation, stakeholder management, and consultative influencing skills.

Ability to work independently, lead initiatives, and influence outcomes across multiple teams.

Experience delivering measurable business improvements through reporting innovation, process optimization, automation, and analytics.

Extensive knowledge of data integrity, governance, and reporting quality practices, including validation, reconciliation, testing, and documentation.

Experience with predictive modeling, advanced analytics, machine learning, AI-enabled reporting, or intelligent automation.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

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