Explore high-impact Senior Vice President, Enterprise Risk Analytics and Reporting Sr. Officer jobs, a pivotal executive role at the intersection of data, technology, and strategic risk governance. Professionals in this senior capacity are responsible for leading the function that transforms raw data into actionable risk intelligence, enabling an organization's board and C-suite to make informed decisions. This position sits at the heart of modern financial and corporate risk frameworks, requiring a unique blend of deep analytical expertise, advanced technological proficiency, and executive leadership. Typically, individuals in these jobs oversee the entire lifecycle of risk information. They lead teams of data scientists, analysts, and developers in designing, building, and maintaining robust analytics platforms and automated reporting suites. A core responsibility is to ensure the accurate and timely aggregation of risk data across the enterprise, which feeds into capital calculations, stress testing, and compliance reporting. They champion the use of Business Intelligence tools like Tableau or Power BI to create intuitive, executive-level dashboards that clearly communicate complex risk exposures, trends, and concentrations. Furthermore, they are often tasked with modernizing the risk technology stack, leading initiatives to remediate end-user computing tools and migrate processes to controlled, scalable platforms. The role demands a strategic leader who can translate business and regulatory requirements into technical specifications and long-term data roadmaps. Common responsibilities include setting the vision for the risk analytics function, managing multi-year data transformation projects, and ensuring all outputs meet stringent regulatory standards (such as Basel, CCAR, or IFRS 9). They act as a crucial bridge, liaising between risk management committees, business heads, and IT departments to align data capabilities with organizational risk appetite and strategic objectives. Candidates for these executive jobs must possess a proven track record in leading high-performing technical teams and a strong background in quantitative disciplines. Extensive hands-on experience with programming languages like Python or R for data analysis and application development is typically essential, coupled with expertise in database management and BI visualization. A solid understanding of financial risk models—covering credit, market, operational, and liquidity risk—is fundamental. Beyond technical acumen, exceptional communication and stakeholder management skills are paramount, as the role involves presenting complex analytical findings to senior management and regulators. A relevant advanced degree in finance, mathematics, computer science, or a related field is commonly required for these influential positions.
