Are you passionate about building innovative products that transform risk management in banking? Join our Credit Risk Innovation team where you’ll combine quantitative modelling, product development, agile delivery, and techno-functional expertise to create next-generation solutions for credit risk analytics and portfolio management. As an Vice President 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. In this role you will lead the development and implementation of advanced risk models for stress testing, risk appetite, IFRS9, and CECL. Using your python programming, AI/ML and analytics solution development skills you will modernise the operating model of the team to optimize our workflows and embed modelling into business decisioning. Our culture is all about thinking outside the box, challenging the status quo and striving to be best-in-class. Job Responsibilities • Build, enhance, and implement credit risk (PD, LGD, EAD etc.) models for stress testing, risk appetite, IFRS9, and CECL, ensuring compliance with regulatory standards and alignment with business objectives. • Architect and develop solutions 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 product and portfolio management, ensuring solutions are data-driven, scalable, and regulatory-compliant. • Partner with risk managers, product, and tech teams across geographies to deliver impactful solutions and drive adoptionIdentify opportunities to automate and streamline risk analytics processes using Generative AI/LLMs, Machine Learning, data engineering, and modern technology stacks.. • 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. • Prepare model documentation, support model governance, and maintain strong control standards throughout the development lifecycle. Required qualifications, capabilities, and skills • 7+ years’ experience in leading model development, implementation, risk analytics, data science and product development. • Proven experience in developing and execution of credit risk processes for stress testing, risk appetite and IFRS9/CECL, ideally covering both corporate and securitized products. • Ability to break down complex business challenges and deliver practical, scalable solutions. • Strong statistical modelling skills, including expertise in techniques such as regression analysis, time series modelling, and probability theory as applied to risk analytics. • Advanced Python/PySpark programming skills, with hands-on experience in model implementation and solution development. • Solid understanding of regulatory requirements and credit risk analytics in banking. • Experience designing and delivering analytics products or platforms, including data pipelines and dashboarding. • Ability to innovate, automate, and optimize risk processes using technology. • Excellent problem-solving, communication, and stakeholder management skills. • Hands-on experience with agile frameworks, sprint planning, and backlog management. • Skilled at translating technical concepts for business stakeholders and driving crossteam collaboration. • Master’s or advanced degree in a quantitative field (e.g., mathematics, statistics, engineering, computer science, finance). Preferred qualifications, capabilities, and skills • Experience in large banking, consulting and financial services is a plus. • Experience implementing, fine-tuning, and integrating AI/ML models with cloud platforms and cloud-native services. • Practical experience in leveraging Generative AI, large language models (LLMs), and driving automation in financial servicesUnderstanding of MLOps practices for deploying, monitoring, and maintaining AI solutions in banking. • Working knowledge of agile tools (JIRA, Confluence) and project management methodologies. About Us JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About the Team Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success
Ctc Modelling Innovation VP
JPMorgan Chase · Banking · Mumbai, Maharashtra, India · Corporate Sector
This Vice President role in JPMorgan Chase's Credit Risk Innovation team focuses on developing and implementing advanced credit risk models and analytics solutions for stress testing, risk appetite, IFRS9, and CECL. The role involves leveraging Python/PySpark, AI/ML, Generative AI/LLMs, and modern technology stacks to modernize operating models, optimize workflows, and embed modeling into business decisioning. The position requires strong quantitative modeling, product development, and agile delivery skills, with an emphasis on regulatory compliance and stakeholder management within a banking context.
What you'd actually do
- Build, enhance, and implement credit risk (PD, LGD, EAD etc.) models for stress testing, risk appetite, IFRS9, and CECL, ensuring compliance with regulatory standards and alignment with business objectives.
- Architect and develop solutions 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 product and portfolio management, ensuring solutions are data-driven, scalable, and regulatory-compliant.
- Partner with risk managers, product, and tech teams across geographies to deliver impactful solutions and drive adoptionIdentify opportunities to automate and streamline risk analytics processes using Generative AI/LLMs, Machine Learning, data engineering, and modern technology stacks.
- Develop product proposals, manage backlogs, prioritize features, and communicate progress to stakeholders.
Skills
Required
- 7+ years’ experience in leading model development, implementation, risk analytics, data science and product development.
- Proven experience in developing and execution of credit risk processes for stress testing, risk appetite and IFRS9/CECL, ideally covering both corporate and securitized products.
- Ability to break down complex business challenges and deliver practical, scalable solutions.
- Strong statistical modelling skills, including expertise in techniques such as regression analysis, time series modelling, and probability theory as applied to risk analytics.
- Advanced Python/PySpark programming skills, with hands-on experience in model implementation and solution development.
- Solid understanding of regulatory requirements and credit risk analytics in banking.
- Experience designing and delivering analytics products or platforms, including data pipelines and dashboarding.
- Ability to innovate, automate, and optimize risk processes using technology.
- Excellent problem-solving, communication, and stakeholder management skills.
- Hands-on experience with agile frameworks, sprint planning, and backlog management.
- Skilled at translating technical concepts for business stakeholders and driving cross team collaboration.
- Master’s or advanced degree in a quantitative field (e.g., mathematics, statistics, engineering, computer science, finance).
Nice to have
- Experience in large banking, consulting and financial services is a plus.
- Experience implementing, fine-tuning, and integrating AI/ML models with cloud platforms and cloud-native services.
- Practical experience in leveraging Generative AI, large language models (LLMs), and driving automation in financial servicesUnderstanding of MLOps practices for deploying, monitoring, and maintaining AI solutions in banking.
- Working knowledge of agile tools (JIRA, Confluence) and project management methodologies.
What the JD emphasized
- regulatory standards
- regulatory-compliant
- regulatory requirements
- Generative AI/LLMs
- AI/ML
Other signals
- Develop product proposals, manage backlogs, prioritize features, and communicate progress to stakeholders.
- Identify opportunities to automate and streamline risk analytics processes using Generative AI/LLMs, Machine Learning, data engineering, and modern technology stacks.
- Integrate advanced risk models and analytics into product and portfolio management, ensuring solutions are data-driven, scalable, and regulatory-compliant.