JP Morgan Chase - Associate - Loss Forecasting Analytics - Consumer Banking

As part of Loss Forecasting team, you will be responsible for understanding the business functioning, get a very good understanding of forecasting models and be able to challenge the model output, enhance and support the loss forecasting function.

You will be responsible to set team goals, work with business partners to ensure timely deliverables as well as initiate value add analytics. Regular work would include developing analytical solutions to enhance forecasting accuracy like benchmark tools, overlay framework, CECL methodology among others.

In this highly visible role, the successful candidate will actively help determine the loss forecasting results and drivers and hold conversations with modeling teams to understand the underlying assumptions and challenge model limitations, if any. This information will be presented to executive management and other internal clients.

Responsibilities include:

- Be part of the high-performing team that leads advanced analyses to assess relationships and patterns driving loss performance and assess performance of existing models.

- Analyze the impact of evolving standards such as Basel capital and CECL on forecast needs and business decisions.

- Understand the functioning of forecasting models and be able to challenge the model by conducting independent model assessment. Coordinate closely with model development teams to provide business perspective and insights.

- Understand how inputs and outputs are generated and ability to modify inputs and output for what if scenario or regression testing of the models.

- Synthesize large volumes of data into actionable insights to influence business strategies for the Chase CCB Wholesale product

- Documenting findings into compelling reports for senior management risk dialogue and escalation.

- Presenting findings, recommendations and presentations to Senior Management.

- Expected to work on multiple projects with limited guidance.

- Effectively mentoring other analysts within same risk team and other risk teams to help them develop their risk management skills and knowledge.

Master's degree in a quantitative discipline; Math, Finance, Statistics, Economics or equivalent work/training is required

- 5+ years of related analytical experience

- Deep credit risk experience in one or more US consumer credit portfolios (i.e. U.S. Mortgage, Home Equity, Credit Card, Automotive, Lease, Business Banking)

- Strong analytical, technical and statistical skills in to credit risk modeling and benchmarking. Ability to synthesize / analyze diverse information, develops recommendations, and makes decisions.

- Project Management Skills - well-organized, structured approach. Ability to achieve tight timelines on complex deliverables. Ability to manage and prioritize projects across cross-functional groups.

- Ability to develop an auditable control framework for the research completed by the team

- Strong communication and interpersonal skills, ability to interact with individuals across departments / functions and with senior-level individuals.

- 3+ years of SAS/R/Python programming experience (PC, UNIX or mainframe).

- Highly proficient in Microsoft Office suite of products.