VP - Credit Modeling & Data Infrastructure - BFS

Role Summary/Purpose:

- Credit and Capital Management group is seeking a credit risk modeling and data analytics professional experienced with developing credit and fraud prediction models per relevant regulatory guidance (SR 11-7 / OCC 2011-12, CECL, CCAR, DFAST). This role is part of Credit and Capital Management Department, supporting the Credit Forecasting & Advanced Analytics function, as well as Credit Strategy COE.

- The role requires demonstrated expertise with data mining and statistical analysis, as well as programming skills (Python/Pandas, Spark, Hadoop, SQL, SAS and equivalent advanced softwares / platforms). The successful candidate will have excellent communication & project management skills, strong model development experience and good understanding of model risk.

- The key focus areas for this role include credit model development, data infrastructure, and data science initiatives, supporting the US function of Credit Forecasting & Advanced Analytics, as well as Credit Acquisition Strategy COE. The model development initiative involves focus on credit loss forecasting, credit reserve models, and customer facing Acquisition, Account management, fraud, deposit and authentication modeling projects.

- As the India team lead, supporting the US Modeling & Data leaders, the role is expected to be an active participant in ongoing projects, leading a direct team of modeling and data practitioners. There is a significant amount of collaboration with the US leadership in executing critical credit estimation models and data initiatives, and active communication with senior audiences.

- The person will approach projects with analytical rigor, coaching their team, appropriately prioritizing deliverables and continuing upskilling their team's knowledge base to advanced techniques & technologies. The projects involve big data, complex statistical & econometric models, as well as consumer scorecard models.

Essential Responsibilities :

Credit Modeling:

- Design and develop consumer credit statistical / econometric models to support production Loss Forecasting, Reserves (CECL), and Stress Testing processes

- Work closely with strategy teams to support inhouse and vendor models through the model lifecycle

- Convert business requirements into modeled solutions, enhancing efficacy and generating insights

- Aid management of models through their lifecycle, from core development phase through to implementation into production, and outline enhancements for evaluation and future model releases.

- Seek out opportunities for model improvements, collaborate on model re-calibrations, and re- fits when business dynamics change

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

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

Data Infrastructure & Sciences :

- Provide support to the data infrastructure monthly processes involving data warehouse loads (RDG) via source systems, and testing the ETL processes

- Support data science initiatives / proof of concept in solving business issues through data mining / utilizing new data sources including dark data

Team Management :

- Managed a direct team, with a focus on prioritizing deliverables / timelines, upskilling talent to latest techniques and technologies, as well as providing cross functional experiences

- Collaborate with US teams - Model Development, Data Infrastructure, as well as Business Process teams (Credit Forecasting, Reserves, Stress Testing, and Credit Strategy)

- Perform other duties and/or special projects as assigned

Qualifications/Requirements :

- Bachelor's degree in quantitative field (i.e., Risk, Accounting, Business, Economics, Finance, Mathematics, Statistics, Engineering) and 10+ years of experience in 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, Credit scorecards or other areas with consumer credit estimation, or analogous areas such as insurance

Desired Characteristics :

- Master's degree in quantitative field (i.e., Risk, Accounting, Business, Economics, Finance, Mathematics, Statistics, Engineering)

- 2+ years of experience in data warehouse ETL processes

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

- Familiarity with US 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

- Managing a team of data scientists or modeling / data practitioners

- Positive mindset under tight timelines / critical deliverables