You enjoy shaping the future of product innovation as a core leader, driving value for customers, guiding successful launches, and exceeding expectations. Join our dynamic team and make a meaningful impact by delivering high-quality products that resonate with clients.
As a Product Manager, Vice President in Corporate & Investment Banking Planning & Analysis Data Transformation and Innovation, you are an integral part of the team that innovates new product offerings and leads the end-to-end product life cycle. You will support product strategy and delivery for data and AI-enabled capabilities, translating user needs into a prioritized backlog and actionable requirements. You will also partner across business, technology, and data teams to improve data consumption patterns and influence decision-making through analytics. Utilizing your deep understanding of how to get a product off the ground, you guide the successful launch of products, gather crucial feedback, and ensure top-tier client experiences. With a strong commitment to scalability, resiliency, and stability, you collaborate closely with cross-functional teams to deliver high-quality products that exceed customer expectations.
Job responsibilities
- Develops a product strategy and product vision that delivers value to customers
- Manages discovery efforts and market research to uncover customer solutions and integrate them into the product roadmap
- Owns, maintains, and develops a product backlog that enables development to support the overall strategic roadmap and value proposition
- Builds the framework and tracks the product's key success metrics such as cost, feature and functionality, risk posture, and reliability
- Develops and executes data and product strategy that delivers value to end users, with emphasis on reporting, analytics, and planning modernization.
- Conducts user interviews, prioritizes user needs, tests ideas, and converts findings into scalable solutions.
- Designs and delivers AI-enabled product capabilities, including experience working with multi-agentic workflows, Model Context Protocol (MCP), and related emerging AI orchestration patterns to drive intelligent automation and decision support.
- Understands financial data models across multiple data products and applies that understanding to define data requirements and acceptance criteria.
- Collaborates and presents technical information in a clear and concise manner to both technical and non-technical audiences, including senior stakeholders.
Required qualifications, capabilities, and skills
- 5+ years of experience or equivalent expertise in product management or a relevant domain area
- Advanced knowledge of the product development life cycle, design, and data analytics
- Proven ability to lead product life cycle activities including discovery, ideation, strategic development, requirements definition, and value management
- Excellent communication skills, effectively conveying complex data concepts to both technical and non-technical stakeholders.
- Demonstrated ability to formulate product strategy, maintain a roadmap, and manage a backlog with clear prioritization rationale.
- Strong understanding of data models and BI tools.
- Financial services industry domain expertise, with comfort operating in complex, highly governed environments.
- Bachelor's degree or equivalent practical experience in a relevant field (e.g., Business, Computer Science, Information Systems, Engineering, Economics).
Preferred qualifications, capabilities, and skills
- Demonstrated prior experience working in a highly matrixed, complex organization
- Knowledge of cloud-based data platforms and technologies such as AWS and Databricks.
- Experience with emerging data consumption tools and patterns, including self-service analytics enablement.
- Experience with AI/ML technologies and their application in product development, including familiarity with large language models, multi-agentic workflows, or AI orchestration patterns and their application in product development.
- Experience translating complex financial data and controls constraints into clear product requirements and testable acceptance criteria.
- Familiarity with business intelligence (BI) tools and experience in SQL for data analysis and reporting