Credit Risk Modelling Associate

Are you passionate about building innovative products that transform risk management in banking? Join our Credit Risk Innovation team where you'll combine product development, agile delivery, and techno-functional expertise to create next-generation solutions for credit risk analytics and portfolio management.

As an Associate in the Credit Risk, you are at the centre of keeping JPMorgan Chase strong and resilient. You will help the firm grow its business in a responsible way by anticipating new and emerging risks. Using your data, analytics and AI expertise, you will modernise the approach of the team to solve real-world challenges that impact our company, customers and communities. Our culture is all about thinking outside the box, challenging the status quo and striving to be best-in-class.

Job Responsibilities

• Lead the end-to-end lifecycle of credit risk analytics products-from ideation, user story mapping, and MVP definition to launch and iteration.
• Architect and develop platforms using Python/PySpark, awareness of cloud technologies (AWS, Azure), and modern front-end frameworks (React, Angular) to deliver robust credit risk tools.
• Integrate advanced risk models and analytics into banking products and portfolios, ensuring solutions are data-driven, scalable, and regulatory-compliant.
• Partner with risk, product, and tech teams across geographies to deliver impactful solutions and drive adoption.
• Leverage AI/ML, LLMs, and automation to enhance credit risk review, underwriting, and monitoring processes.
• Develop product proposals, manage backlogs, prioritize features, and communicate progress to stakeholders.
• Work in cross-functional squads, apply agile methodologies (Scrum, Kanban), and iterate quickly based on stakeholder feedback.

• 5 years' experience in product development, data science, or credit risk analytics with Bachelor's degree in a quantitative or technical field (CS, engineering, math, etc.).
• Experience in product management or product development, ideally in risk analytics or banking technology.
• Proficiency in Python/PySpark, cloud platforms, data visualization (Tableau), and front-end/back-end development.
• Solid understanding of credit risk, banking products, portfolio analytics, and regulatory requirements.
• Hands-on experience with agile frameworks, sprint planning, and backlog management.
• Ability to break down complex business challenges and deliver practical, scalable solutions.
• Skilled at translating technical concepts for business stakeholders and driving cross-team collaboration.

• Practical experience with Generative AI, large language models (LLMs), and automation in financial services.
• Hands-on expertise with NLP frameworks (e.g., Hugging Face Transformers, spaCy, NLTK) and prompt engineering for generative AI.
• Knowledge of Retrieval-Augmented Generation (RAG) architectures and enterprise AI applications.
• Experience implementing, fine-tuning, and integrating AI/ML models with cloud platforms and cloud-native services.
• Solid understanding of MLOps practices for deploying, monitoring, and maintaining AI solutions.
• Strong UI/UX and dashboarding skills.
• Proficient with agile tools (JIRA, Confluence) and project management methodologies.