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 with a focus on innovation and compliance.
- Benefits: Competitive salary, career growth opportunities, and a dynamic work environment.
- Other info: Collaborate with diverse teams and enhance your skills in a fast-paced setting.
- Why this job: Make a real impact in credit risk decision-making while working with cutting-edge technology.
- Qualifications: Experience in data product delivery and strong understanding of data governance.
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 employer: Jpmorgan Chase & Co.
As a Vice President Data Product Owner in the Credit Risk team, you will thrive in a dynamic and innovative environment that prioritises employee growth and collaboration. Our commitment to fostering a culture of excellence is reflected in our robust training programmes, competitive benefits, and a focus on work-life balance, all set within a vibrant corporate hub. Join us to make a meaningful impact while advancing your career in a supportive and forward-thinking organisation.
StudySmarter Expert Advice🤫
We think this is how you could land Credit Risk Data Product Owner - Vice President
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people 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 storytelling skills! Be ready to share specific examples of how you've tackled challenges in data product delivery or governance. This will help you stand out and demonstrate your expertise.
✨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
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Credit Risk Data Product Owner. Highlight your experience with 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 credit risk and how your skills align with our needs. Be specific about your experience with structured credit instruments and how you can contribute to our team.
Showcase Your Technical Skills:Don’t forget to mention your technical expertise! If you’ve worked with SQL, Python, or cloud data platforms, make sure to highlight these skills. We want to see how you can help us develop AI-ready datasets.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and get you into our system quickly!
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Know Your Data Products Inside Out
Make sure you have a solid understanding of structured credit risk data products. Familiarise yourself with the specific data governance, lineage, and compliance requirements mentioned in the job description. This will help you demonstrate your expertise and show that you're ready to take ownership of the product lifecycle.
✨Prepare for Stakeholder Conversations
Since this role involves collaborating with various stakeholders, practice how you'll communicate complex data concepts to both technical and non-technical audiences. Think about examples from your past experience where you've successfully translated business needs into data solutions, as this will showcase your strong stakeholder management skills.
✨Showcase Your Technical Skills
Brush up on your SQL and Python skills, as well as your knowledge of AI and machine learning concepts. Be prepared to discuss how you've used these tools in previous roles to support data quality monitoring or analytics. This will highlight your hands-on experience and technical proficiency.
✨Demonstrate Your Governance Knowledge
Be ready to talk about your experience with data governance frameworks and compliance in regulated environments. Prepare specific examples of how you've implemented data contracts, monitored data quality, or ensured audit readiness. This will show that you understand the importance of governance in delivering reliable data products.
