We are looking for a risk modeling professional to deliver client facing projects/engagements in quantitative model development projects including full development, re-development, calibration and fit for use assessment of models in the risk and regulatory area. This would involve application of various industry best practices and techniques in risk modeling including but not limited to linear/ logistic regression, time series methods, Markov chain, survival modelling and machine learning techniques.
The selected candidate will work with leading banking clients to support varied model development needs in a fast paced environment, bring in critical thinking, expertise in modeling and industry best practices. Charter of the role spans:
Work hands-on for critical risk modeling projects as well support team’s project deliverables with statistical and domain expertise
- Works hands-on in development, re-development and calibration of risk and regulatory models, including but not limited to Credit Decision Scorecards, Basel IRB – PD, LGD, EAD, Stress Testing, IFRS 9/CECL models
- Develop presentations to be shared with senior client management
- Data and quantitative analysis to support modeling decisions
- Leading development of model methodologies, algorithms and diagnostic tools for testing model robustness, sensitivity and stability
- Detailing model techniques and interpretation of variables used in the models to be documented and presented to client Stakeholders
- Validation for the source data quality, forecast data quality as well as change management
- Helping develop thorough technical documents for distribution and presentation to senior management, model developers, auditors and regulators
- Bringing in industry best practices and consultative inputs to help deliver continuous value to client engagements in advanced risk analytics
Required Skills :
- 5+ years’ experience in BFS analytics, with 3+ years’ experience in credit risk modeling
- Excellent knowledge of various statistical techniques and core hands-on experience in statistical modeling (Logistic Regression, GAM, Time series, Survival Techniques – Competing Hazard, COX proportional hazard, Clustering, CHAID/Classification trees Etc.)
- Good client management and communication/presentation skills – written & verbal
- Master’s degree in quant discipline - Statistics/Economics/Finance/Mathematics
- Ambitious, proactive, “can-do” attitude. Ability to work under ambiguity and with minimal direct supervision.
- Expertise in SAS, SQL, Python
- Hands-on experience in Machine Learning (Boosting, Bagging techniques) modeling is a plus
- Experience in visualization technologies Tableau, Spotfire, MATLAB and SPSS is a plus
- Ability to work independently on complex core modeling projects
- Experience in credit risk/regulatory model development – CECL, IFRS 9, Stress Testing, AIRB
- Consultative mindset and experience in client interfacing with strong interpersonal skills
- Project management experience
- Must be articulate and confident to manage senior stakeholder conversations
