Vice President - Statistical Modeling - Credit Risk - BFSI

Overall purpose of role

- Support the development, calibration, monitoring and documentation of credit risk models in line with regulatory requirements, e.g. Basel, CRR, CCAR, IFRS9

- Enhance model management through automation and development of monitoring packages

Key Accountabilities :

- Calibrate new credit risk models, contributing to the development through approval

- Validate performance of new models; develop and deploy model monitoring scripts

- Maintain model documents to required standards

- Manage parts of complex projects, liaising with stakeholders to ensure project progress

- Motivate team members and junior staff to deliver high quality output within tight deadlines

Stakeholder Management and Leadership :

- Manage stakeholder expectations with respect to dependencies and deliverables

- Keep open dialogue with model owners, developers and validation teams on model work and reviews

- Mentor and lead junior members of the team, ensuring they are trained on modelling datasets, regulation, documentation and are able to deliver quality output and presentations to stakeholders.

- Lead project meetings, provide clear plan on future steps and guide colleagues through actions

- Decision-making and Problem Solving

- Adapt quickly to new environments and systems

- A keen eye for detail

- Self-starter: motivated and disciplined

- Able to work autonomously and within a team environment, as required

- Manage multiple requirements and prioritise appropriately

Risk and Control Objective :

- Ensure that all activities and duties are carried out in full compliance with regulatory requirements

Person Specification

- Has developed, validated, reviewed or applied statistical models within credit risk domain

- Understands the quantitative techniques used in developing and validating PD, LGD, and/or EAD models

- Demonstrates ability to work in an environment where modeling decisions are regularly challenged

- Track record of producing high quality written communication including results of research and presentations for technical and non-technical audiences

Essential Skills/Basic Qualifications:

- Post-graduate degree in a quantitative discipline, such as Statistics, Mathematics, Econometrics, Physics, Engineering, with experience of developing and applying statistical models within credit risk domain

- Excellent knowledge of statistics, e.g. regression analysis, reject inference, decision trees, confusion matrix, cross-validation

- Numerical programming ability using R and/or Python, and working experience with SQL

- Experience in data visualization, cleaning, and feature extraction

Desirable skills/Preferred Qualifications:

- Experience with the Latex document preparation system

- Knowledge of at least one static typed language; C++, Java, C# or other programming languages

- Familiar with continuous integration development framework (e.g. Teamcity), and source control (P4, Git, SVN)

- Familiar with unit-testing