Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area This is a unique opportunity for you to work in our team to partner with the Business to provide a comprehensive view.

As a Quantitative Research Associate within the Wholesale Credit QR team, you will be part of a mission to design, analyze, and deliver risk-management quantitative models to support the firm's Wholesale Credit Stress (CCAR, ICAAP, Risk Appetite) and loan loss reserves models. In this role, you will focus on analysis, design, development, and maintenance of quantitative statistical models, forecasting losses and reserve calculations for JP Morgan's Wholesale Loan Portfolio. You will be responsible for understanding business requirements, analyze, transform & process data sources, use statistical techniques & tools for building forecasting models & implementing/maintaining the model (or suite). You will be responsible for using internal strategic data, modelling, and implementation platforms for your day-to-day work. This role will provide you with the opportunity to work with other experienced Wholesale Credit model developers and business partners, enhancing your quantitative as well as business skills.

Job Responsibilities

• Work as a quantitative researcher to analyze, design and deploy statistical loss forecasting models for regulatory purposes
• Understand business requirements, develop solutions/analysis, & validate/deploy. Perform data analysis to support model development and analytics
• Implement model methodologies on in-house strategic loss forecasting framework.
• Perform on-going performance monitoring of deployed models and re-reviews of existing models
• Collaborate through the entire Model Review & Governance process including documentation, knowledge sessions, experiments & feedback loops

Required qualifications, capabilities, and skills

• Bachelor's or Master's in Computer Science, Mathematics, or related fields. Minimum 3 years in quantitative research, model validation or development in financial firms/products
• Knowledge of statistical & Machine Learning tools & techniques for building, enhancing & maintaining loss forecasting models for regulatory exercises like CCAR, ICAAP, BASEL etc.
• Experience implementing analytics frameworks in finance.Experience with source control, automated build/test systems, code coverage, unit testing and release processes
• Ability to solve problems creatively while working in a dynamic environment. Eagerness to learn about Credit Risk, Risk Parameters, Regulatory and Accounting concepts
• Detail oriented and strong organizational skills.Excellent communication abilities, both written and oral

Preferred qualifications, capabilities, and skills

• Knowledge of Wholesale Credit, CCAR, Allowance (IFRS 9/CECL), Basel II/III regulatory capital requirements
• Proven ability to develop collaborative relationships with key internal partners to achieve objectives and prioritizations

Skills: Machine Learning, Unit Testing, Analytics, Basel, icaap , Regulatory, code coverage , CCAR, Accounting, Source Control, Credit Risk

Experience: 3.00-5.00 Years