As an Analytics Solutions Manager in the Commercial & Investment Bank, you will primarily lead the creation and continuous improvement of best-fit data products and delivery solutions to enhance the effectiveness and efficiency of Global Banking employees. You will interface with business leadership to prioritize and deliver solutions using a combination of existing data assets, while also identifying new capabilities that need to be developed—sometimes directly leading the development of these new capabilities. As the role combines aspects of product management and business process/operations, you will have demonstrated consistent success in developing and delivering data-driven solutions in a dynamic, cross-functional environment.

Responsibilities

• Design and maintain standardized, reusable client-level signal models supporting Client Onboarding & Service and overall, Client Wellness
• Build reliable pipelines producing governed signals, scores, and event triggers
• Operationalize and scale client-level signals, trend detection, and predictive intelligence across Front Office, Middle Office, Product, Marketing, and Business Management teams
• Translate signals into actionable outputs for CRM, service tools, dashboards, and alerts
• Act as the technical integrator across Data Science, Client Experience, and Sales
• Establish standards for data quality, lineage, explainability, to deliver a consistent single version of truth
• Partner with cross-functional stakeholders to deliver high-impact insights and analytics in support of business process integration/data strategy

Required Qualifications, Skills, and Capabilities

• 5–10 years in data engineering, analytics engineering, or data product management
• Deep SQL and data modeling expertise
• Experience with modern cloud data platforms and event-driven architectures
• Proven ability to translate ambiguous business needs into scalable solutions
• Demonstrated ability to communicate effectively at multiple levels of management, both written and verbal, across technical and business stakeholders
• Systems thinker with a strong product mindset
• Comfortable operating in ambiguity and influencing without authority
• Bias for action with high standards for data quality and credibility