HR Recruiter at Black Turtle
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Vice President - Statistical Modeling - Credit Risk - BFSI (9-14 yrs)
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
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