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Product Associate, Global Private Banking Chief Data Office (CDO)
mid · Technology / Software Development
Join our collaborative environment, where you'll contribute to our strategy and make an impact on product success. Grow your skills, participate in product planning, and define user workflows while working alongside experienced product managers. Don't miss this opportunity to be part of a dynamic team and promote innovation in customer experiences.
As a Product Associate in Global Private Banking Chief Data Office (CDO) group, you play a crucial role in supporting the product development process and contributing to the discovery of innovative solutions that address customer needs. Working closely with the product management team and cross-functional partners, you contribute your skills and insights to help ensure the success of our product offerings. As a valued member of the team, you have the opportunity to learn and grow in a dynamic and fast-paced environment, making a tangible impact on our products and customer experiences.
You contribute to the team by leveraging your expertise in product development and optimization to make a significant impact, supported by user research and customer feedback to fuel the creation of innovative products and continuously improve existing offerings. Collaborate closely with cross-functional teams and play a crucial role in shaping the future of our products and ongoing success.
Job responsibilities
- Supports the development of our product strategy and roadmap
- Collects and analyzes metrics on product performance to inform decision-making
- Contributes to solution discovery through collaboration with cross-functional teams to identify potential solutions that address user needs and align with business goals
- Participates in product planning sessions, contributes ideas and insights, and assists in the execution of product initiatives, ensuring timely and successful product launches
- Collaborates with product managers, stakeholders, and cross-functional teams to define user workflows, requirements, epics, and user stories, ensuring alignment to customer value.
- Partners on product discovery and user research, including journey mapping and market analysis, to identify new opportunities and inform the product roadmap.
- Analyzes, tracks, and reports on product and operational metrics (e.g., time, cost, quality, performance trends) to support continuous improvement.
- Supports Data Quality operations, including executing and monitoring TDQ/BDQ checks, analyzing results, and driving issue detection, root cause analysis, and remediation.
- Maintains data quality governance artifacts, including centralized rule registries, traceability, audit evidence, and recertification support.
- Builds and maintains reporting, dashboards, and scorecards to track quality trends, coverage, SLAs, and overall data health.
- Drives enablement, adoption, and transparency by collaborating across business and technology teams, providing guidance, and surfacing data quality insights to stakeholders.
Required qualifications, capabilities, and skills
- 2+ years of experience or equivalent expertise in product management, project management, or a relevant domain area.
- Developing knowledge level of the product development life cycle.
- Exposure to product life cycle activities including discovery and requirements definition.
- Emerging knowledge of data analytics and data literacy.
- experience in data management, analytics, or related roles (internships and academic projects count).
- Familiarity with data quality concepts, data profiling, and data governance.
- Demonstrated experience with SQL and Python, along with proficiency in other data analysis tools.
- Strong analytical, problem-solving, and communication skills.
- Ability to work collaboratively in a fast-paced, matrixed environment.
- Interest in financial services, asset management, or wealth management.
Preferred qualifications, capabilities, and skills
- Demonstrates a strong interest in leveraging emerging technologies, such as AI, large language models (LLMs), and intelligent agents, to enhance efficiency and effectiveness across day-to-day job responsibilities.
Experience with data quality tools and reporting platforms.
Understanding of metadata, data contracts, and centralized rule registries.