At a Glance
- Tasks: Lead the creation of AI-ready credit risk data products and ensure quality governance.
- Company: Join a leading financial services firm focused on innovation and compliance.
- Benefits: Competitive salary, career growth, and opportunities to work with cutting-edge technology.
- Other info: Collaborative culture with opportunities to work across teams and enhance your career.
- Why this job: Make a real impact in credit risk decision-making while developing your skills in a dynamic environment.
- Qualifications: Experience in data products and strong understanding of data governance required.
The predicted salary is between 80000 - 100000 £ per year.
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.
Credit Risk Data Product Owner - Vice President in London employer: J.P. Morgan
Join a forward-thinking organisation that prioritises innovation and excellence in the financial services sector. As a Vice President Data Product Owner, you will thrive in a collaborative work culture that values your expertise and encourages professional growth through continuous learning and development opportunities. Located in a vibrant city, our company offers competitive benefits and a commitment to fostering a diverse and inclusive environment, making it an exceptional place to build a meaningful career in credit risk management.
StudySmarter Expert Advice🤫
We think this is how you could land Credit Risk Data Product Owner - Vice President in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend events, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for interviews by researching the company and its culture. Understand their approach to credit risk and data governance. This will help you tailor your answers and show that you're genuinely interested in the role.
✨Tip Number 3
Practice your pitch! Be ready to explain how your experience aligns with the responsibilities of a Data Product Owner. Highlight your skills in data governance, compliance, and stakeholder management to make a strong impression.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Credit Risk Data Product Owner - Vice President in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Credit Risk Data Product Owner role. Highlight your experience in data governance, compliance, and any relevant projects that showcase your ability to deliver data products in a regulated environment.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about building AI-ready data products. Share specific examples of how you've successfully managed data products or led teams in similar roles, and don’t forget to mention your understanding of structured credit instruments!
Showcase Your Technical Skills:Since this role involves working with SQL, Python, and cloud data platforms, make sure to highlight your technical expertise. Include any relevant projects or experiences where you’ve used these skills to solve problems or improve processes.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our team and culture!
How to prepare for a job interview at J.P. Morgan
✨Know Your Data Products Inside Out
Before the interview, dive deep into the specifics of structured credit risk data products. Understand their lifecycle, governance, and how they impact decision-making. This knowledge will help you articulate your vision and strategy effectively.
✨Showcase Your Stakeholder Management Skills
Prepare examples that highlight your experience in managing stakeholders across different teams. Be ready to discuss how you've translated complex technical concepts into business-friendly language, as this is crucial for a Data Product Owner role.
✨Demonstrate Your Compliance Knowledge
Brush up on data governance, compliance, and audit readiness. Be prepared to discuss how you've implemented these practices in previous roles, especially in regulated environments. This will show your understanding of the importance of data quality and controls.
✨Familiarise Yourself with AI and Machine Learning Concepts
Since the role involves developing AI-ready datasets, make sure you can discuss relevant AI and machine learning concepts. Highlight any experience you have with these technologies, and be ready to explain how they can enhance credit risk analytics.
