Finance Data Analytics and Utility - SVP

Citi•Tampa, FL

About The Position

Responsibilities may include staff management, resource allocation, and work distribution within the team. Workflow Enhancement & Data Analytics Participate in assessing and incorporating changing business, regulatory, and market information needs into finance processes and applications. Provide advice to internal clients on the implications of business trends, issues, operating environment changes, and firm or business unit strategy. Ensure all data discovery, reconciliation products, and AI tools strictly adhere to financial and regulatory reporting standards and internal compliance frameworks, demonstrating the integrity of financial books and records through testing and substantiation. Oversee the integration of compliance and audit requirements directly into the product design and delivery process, focusing on transparent and auditable reconciliation outcomes. Define and drive the long-term product vision and strategy for financial data profiling and AI tools, ensuring alignment with organizational goals for financial control, reconciliation, and advanced analytical capabilities. Proactively identify and assess market trends, emerging AI/ML technologies, and automation opportunities to enhance data discovery testing and substantiation processes. Translate complex business requirements related to financial ledger data discovery, reconciliation/proving, workflow optimization, and data analytics into a clear, actionable product roadmap. Develop and manage the product lifecycle for data discovery and reconciliation tools, enforcing and delivering solutions that accurately depict data elements, structures, processes, and differences between legacy and target finance ledger systems. Leverage expertise in AI/ML frameworks, workflow automation platforms, and advanced data analytics tools to optimize the identification, analysis, and resolution of reconciliation differences. Explore and integrate cutting-edge AI-powered solutions for scalable and intelligent financial data utility. Possess a strong understanding of financial data architecture, data modeling, and advanced data analytics techniques. Guide the implementation of robust data controls, data lineage, tracing, and data quality rules specifically for comparative analysis and reconciliation processes.

Requirements

10+ years of relevant experience, preferably within the financial services industry.
In-depth knowledge of financial books and records, consolidated ledger reporting, and the intricacies of reconciliation processes between diverse financial systems, within a global financial institution.
Expertise in designing and implementing advanced data analytics solutions, workflow automation, and integrating AI/ML models for financial data processing, comparison, and reconciliation.
Experience with Python, KNIME, Generative/Agentic Artificial Intelligence applications (preferably in an implementation role).
Demonstrated ability to perform complex data analysis, identify patterns, quantify differences, and derive actionable insights from large financial datasets.
Demonstrated ability to define product strategy, develop roadmaps, and drive execution in complex, fast-paced environments, with a focus on delivering AI-enabled data utility tools for financial reconciliation.
Exceptional written and verbal communication, negotiation, and stakeholder management skills, with proven ability to deliver compelling presentations and engage effectively with C-Suite leaders.
Proven ability to implement and manage data lineage, robust data quality frameworks, and exception resolution processes for critical financial reconciliation data.
Proficiency in product management tools (e.g., JIRA, Confluence) and agile development methodologies.
Bachelor's degree required; Master's degree preferred.
Accounting / Auditing background preferred.
Assessment
Change Management
Communication
Credible Challenge
Management Reporting
Problem Solving
Program Management
Risk Management
Stakeholder Management
Strategic Planning

Nice To Haves

In-depth knowledge of banking products and systems is highly preferred.
Master's degree preferred.
Accounting / Auditing background preferred.

Responsibilities

Staff management, resource allocation, and work distribution within the team.
Participate in assessing and incorporating changing business, regulatory, and market information needs into finance processes and applications.
Provide advice to internal clients on the implications of business trends, issues, operating environment changes, and firm or business unit strategy.
Ensure all data discovery, reconciliation products, and AI tools strictly adhere to financial and regulatory reporting standards and internal compliance frameworks
Oversee the integration of compliance and audit requirements directly into the product design and delivery process
Define and drive the long-term product vision and strategy for financial data profiling and AI tools
Proactively identify and assess market trends, emerging AI/ML technologies, and automation opportunities to enhance data discovery testing and substantiation processes.
Translate complex business requirements related to financial ledger data discovery, reconciliation/proving, workflow optimization, and data analytics into a clear, actionable product roadmap.
Develop and manage the product lifecycle for data discovery and reconciliation tools
Leverage expertise in AI/ML frameworks, workflow automation platforms, and advanced data analytics tools to optimize the identification, analysis, and resolution of reconciliation differences.
Explore and integrate cutting-edge AI-powered solutions for scalable and intelligent financial data utility.
Guide the implementation of robust data controls, data lineage, tracing, and data quality rules specifically for comparative analysis and reconciliation processes.