Are you passionate about building governed, AI‑ready data products that strengthen credit risk decisioning? Join the Credit Risk team in Corporates, Treasury and Chief Investment Office as a Data Product Owner. In this role, you will lead the definition, delivery, and adoption of structured credit risk data products. You will ensure rigorous governance, lineage, controls, and quality monitoring. Your work will enable portfolio surveillance, executive reporting, and scalable analytics and AI use cases.
As a Vice President Data Product Owner in the Credit Risk team within TCIO, you will own the strategy and execution for prioritized credit risk data products across structured credit, leveraged loans, and related investment assets. You will work closely with Credit Risk specialists to build your understanding of products and business needs, while defining scope, data contracts, metadata, and end‑to‑end lineage. You will implement data quality, controls, and governance to support audit and regulatory expectations. You will partner with Risk Management & Compliance stakeholders, data consumers, and Technology to deliver a structured roadmap and drive adoption of standardized data products.
Job responsibilities
- Own the end‑to‑end lifecycle of structured credit risk data products, including vision, roadmap, prioritization, delivery, and adoption
- Act as the business‑aligned data producer; define product scope, data contracts, semantic definitions, and documentation
- Lead data governance and compliance across definitions, ownership, metadata, lineage, access controls, privacy, and audit readiness
- Establish traceable, auditable end‑to‑end lineage to support executive reporting and regulatory exercises
- Define and monitor critical data elements, data quality rules, thresholds, and alerting
- Maintain SLAs for data timeliness, completeness, and accuracy
- Drive triage and remediation of data issues, ensuring sustainable fixes through governance and engineering partnership
- Translate risk and surveillance requirements into epics, user stories, and acceptance criteria; perform testing and validation
- Partner with Technology to develop AI‑ready datasets for surveillance and analytics use cases
- Define standards for AI and machine learning feature consumption with appropriate metadata and context
- Collaborate with cross‑LOB stakeholders to align on requirements, governance ownership, and promote reuse of data products
Required qualifications, capabilities, and skills
- Significant experience delivering data products in a regulated financial services environment
- Strong background in data governance and compliance including metadata, lineage, access controls, and audit readiness
- Experience supporting risk reporting or regulatory deliverables with traceable data and control evidence
- Working knowledge of structured credit instruments and related datasets
- Understanding of AI and machine learning concepts to support analytics and feature consumption standards
- Strong stakeholder management and communication skills with the ability to translate between business and technical teams
Preferred qualifications, capabilities, and skills
- Experience with cloud data platforms and lakehouse architectures, including Databricks
- Knowledge of data modelling, orchestration, and observability concepts
- Hands‑on experience with SQL and data analysis
- Proficiency in Python for data validation and analysis
- Experience implementing data contracts and data quality monitoring tools
- Familiarity with catalog‑driven governance frameworks
- Advanced degree in a quantitative or technical field such as Data Science, Engineering, Physics, or Finance