Overview
As the asset servicing industry undergoes digital transformation, the ability to harness data and artificial intelligence (AI) has become a strategic imperative. From custody and fund administration to securities lending and regulatory reporting, data is the foundation of operational excellence, client service, and innovation. To lead this transformation, we elevating the Chief Data and AI Officer (CDAO) role—to a single executive level leader responsible for unlocking the full value of data and AI across the enterprise.
Strategic Rationale
1. Data as a Core Business Enabler
• Asset servicing firms manage trillions in assets and process vast volumes of transactional, market, and reference data daily.
• A CDAO will ensure this data is accurate, timely, and actionable—supporting everything from NAV calculations to client reporting, corporate functions compliance.
2. AI to Drive Operational Efficiency and Risk Reduction
• AI can automate complex, manual processes such as reconciliations, corporate actions processing, and exception management.
• The CDAO will lead the deployment of AI and machine learning to reduce operational risk, improve turnaround times, and lower costs.
3. Client Expectations and Differentiation
• Institutional clients increasingly demand real-time insights, predictive analytics, and personalized reporting.
• The CDAO will drive the development of data-driven client solutions, enhancing service quality and competitive differentiation.
4. Regulatory Complexity and Data Governance
• The regulatory environment (e.g., SEC, ESMA, Basel III) demands robust data lineage, auditability, and transparency.
• The CDAO will establish enterprise-wide data governance frameworks to ensure compliance and reduce regulatory risk.
5. Enterprise Architecture & Platform Oversight
• Lead the design of scalable data lakehouses, APIs, and AI platforms to support client and operational needs.
• Partner with the CIO, CTO and CISO to ensure data infrastructure is secure, resilient, and compliant.
6. Strategic Insights and Product Innovation
• By integrating internal and external data sources, the CDAO can enable advanced analytics for product development, client behavior analysis, and market intelligence.
• This will support strategic decision-making and open new revenue streams.
Key Responsibilities
• Develop and execute a data and AI strategy.
• Lead enterprise data governance, quality, and architecture initiatives.
• Oversee AI innovation in areas such as automation, predictive analytics, and client intelligence.
• Ensure compliance with global data privacy and financial regulations.
• Partner with operations, technology, risk, and client service teams to embed data and AI into core workflows.
Expected Outcomes
• Operational Excellence: Reduced manual effort, faster processing, and fewer errors.
• Client Value: Enhanced reporting, insights, and service personalization.
• Regulatory Readiness: Stronger data controls and auditability.
• Innovation: New data-driven services and monetization opportunities.
• Strategic Agility: Faster, insight-driven decision-making across the enterprise.

Salary Range:

The range quoted above applies to the role in the primary location specified. If the candidate would ultimately work outside of the primary location above, the applicable range could differ.

Job Application Disclosure:

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.