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Supports financial analytics, period close activities, forecasting, variance analysis, performance metrics, scorecard reporting, and periodic financial reporting. Identifies financial trends, interprets findings, and summarizes business performance for assigned lines of business, corporate functions, or regions. Provides guidance to less experienced team members while maintaining the accuracy and quality of personal work.

Leads business data architecture and reference data design across clients, parties, legal entities, accounts, contracts, products, and related structures. Defines conceptual and logical models, identifiers, entity resolution, authoritative sources, lifecycle processes, stewardship, controls, and operating models. Uses SQL and data profiling to validate data relationships and quality, develops prototypes, and translates business needs into engineering-ready requirements. Partners with Product, Operations, Architecture, Data, and Engineering teams to drive adoption and implementation decisions.

Perform fund/client accounting for assigned, moderately complex funds: calculate NAVs and performance, allocate expenses, reconcile cash/assets, draft and review client reports, drive process improvements and provide guidance to junior staff.

Lead design and implementation of internal audit methodology for Enterprise Custody Services, embed AI and advanced analytics into audit practices, maintain IA policies/procedures, conduct self-assessments against regulatory standards, build relationships across audit teams, and support global audit leadership to improve risk identification, testing efficiency, and audit coverage.

Lead the design, implementation, and continuous improvement of operational risk event and metrics programs. Integrate risk events, limits, indicators, policies, procedures, training, workflows, reporting, and remediation processes. Ensure regulatory alignment, strengthen first- and second-line execution, analyze cross-program risk data, and present actionable insights to senior leaders and governance committees. Build partnerships across business units and risk functions to embed effective operational risk practices.

Leads the design and development of full-stack applications supporting sanctions screening and payment compliance. Builds scalable microservices, APIs, and event-driven systems using cloud-native technologies, containers, automation, and observability. Partners with compliance, product, operations, and architecture teams to deliver regulatory capabilities. Ensures quality through testing, code reviews, and CI/CD, while providing technical mentorship and influencing platform architecture and technology strategy.

Develop and implement client service strategies, improve operational efficiency and satisfaction, ensure regulatory compliance, resolve complex client issues, advise internal teams, and analyze feedback and operational data to support strategic decisions.

Leads client processing operations, managing institutional client relationships, service requests, exceptions, settlement inquiries, account onboarding, and issue resolution. Collaborates with Operations, Risk, Compliance, Technology, and other stakeholders to remediate complex issues. Maintains procedures, metrics, reporting, and operational controls while identifying process improvements and ensuring accurate processing within market deadlines.

Supports application stability and resilience by developing automation workflows, improving scripts and validation checks, onboarding applications into standardized support frameworks, troubleshooting production issues, and implementing durable fixes. The role also contributes to operational playbooks, documentation, pipelines, tooling, and process improvements while mentoring junior team members and strengthening operational controls.

Designs and maintains data models, databases, dictionaries, ETL workflows, and data quality processes. Partners with data owners and reporting teams to define requirements, resolve discrepancies, establish stewardship, and improve data sharing. Develops scalable PySpark and Python pipelines, optimizes SQL and Spark jobs, and implements AI/ML solutions using technologies including Snowflake and Oracle. Requires collaboration across teams, strong documentation, and adherence to data standards.