AVP - Credit Modeling - Reserves & LF

Position: AVP - Credit Modeling (Reserves & LF)

Role Summary/Purpose:

- Financial Credit and Capital Management group is looking for a data scientist / credit risk modeling professional responsible for executing, maintaining and developing models under the relevant regulatory guidance (SR 11-7 / OCC 2011-12, CECL, CCAR, DFAST). This role is part of Credit and Capital Management, in the Credit Forecasting & Advanced Analytics team.

- The role requires experience with big data, statistical analysis and model development, as well as programming skills (Python/Pandas, Spark, Hadoop, SQL, SAS). The primary focus of this role is the model execution supporting the quarterly reserve development process, and models underpinning the loss forecasting estimate projections.

- A secondary focus area is to support the model development team with model builds, enhancements and remediation's as needed. The role is responsible for executing critical credit estimation models on a quarterly basis, providing analytical input to development of estimates of Credit and Fraud Losses by executing complex statistical, trend-based models with forward looking features.

- This role analyses trends and drivers of changes across the entire portfolio and all products. In addition, robust collateral is required to be produced in support of process risk controls and related documentation as part of effective governance, as well as internal and external review.

- The role will collaborate across different functions in Credit & Capital Management, with IT and model development to manage model enhancements and big data processing.

- The person will use their model knowledge, business analysis and process experience to ensure business intent is matched with sound estimates, and communicate with peers and functional leaders, as well as document assumptions and methods to meet accounting rules and model risk management guidelines.

- In addition to responsibilities on scheduled quarterly cycles involving forecasting models, this role will be expected to work on ad-hoc projects as needed such as in Stress Testing models and enhancements to existing model and occasionally, new development initiatives.

- This is a great opportunity for a modeler / statistician / data analyst / programmer with experience in consumer credit analysis. We offer a dynamic, collaborative team environment with a strong credit risk management culture, and exposure to new technology and data platforms.

- A successful candidate must have strong programing skills to execute and troubleshoot data / modeling nuances, design and develop new processes as part of new model implementation(s) and drive process efficiency.

- This roleworks closely with process/model owners, and model development in testing of models, supports validation efforts as well as provides audit support. This position is open to all India hybrid, hoteling, and virtual hub locations.

Essential Functions / Responsibilities:

- Plan and execute models in the production Reserves and Loss Forecasting process with a focus on CECL, as well as allied quantitative estimates such as recoveries and scenario management and stress testing

- Maintain model data input monitoring, production controls and output analytics including results analysis along with robust documentation of key facets

- Support quarterly review process and quarter closing activities, as well as contribute to effective process controls as peer reviewer

- Visualize insights, performance, and trends in inputs/outputs for effective communication and decisioning

- Drive understanding of drivers and providing narrative support for the assumptions, rationale, and projections to model owners and sponsors

- Assist with responding to model validation, regulatory or other oversight requests, including exam findings or issues. Adhere to and follow model governance standards

- Support the development of new models or enhancements to existing models

- Aid management of models through their lifecycle, from development phase through to implementation into production and outline enhancements for evaluation and future model releases. Meet project timelines, engage in ongoing analysis, find performance thresholds, manage model version control, performance assessments, seek out opportunities for process and model improvements, collaborate on model re-calibrations, and re-fits when business dynamics change

- Collaborate with other cross functional teams - Forecasting an, Reserve and Stress Testing/Capital Management teams, Model Development, Data Governance, Finance, Collections and Controllership

- Perform other duties and/or special projects as assigned

Qualifications / Requirements:

- Bachelor's degree with quantitative underpinning (i.e., Data Science, Computer Science, Risk, Accounting, Business, Economics, Finance, Mathematics, Statistics, Engineering) with 8+ years of experience in Programming / Analytics ideally in support of Risk, Credit, Finance, Accounting, Consumer Lending, or other relevant professional experience

- Strong programing skills in SQL, Python, Spark with 5+ years' experience. Proven hands on experience utilizing using SQL, Python, Spark, SAS, to perform statistical analysis, query relational databases, and manage large amounts of data

- 3+ years of experience in credit loss modeling in areas such as Loss Forecasting, Allowance, Stress Testing, or other areas with consumer credit estimation.

Desired Qualifications:

- Excellent time management with ability to manage multiple competing initiatives and deliver results within deadlines with accuracy and attention to detail

- Experience in process improvement, project management or change management

- Familiarity with Model Governance trends/developments across the banking sector, especially as related to credit card or consumer lending (SR11-7)

- Strong communication skills to facilitate complex discussions in productive and collaborative manner

- Positive mindset under tight timelines and critical deliverables

- Experience with Linux, HDFS and AWS to collaborate and operate in a cloud computing environment