Analyste princ., Modélisation et Prévisions; Analyses quant

Détails De La Rémunération

$76,800 - $115,200 CAD

Department Overview: The Retail Expected Loss Model Development group within the TD Bank Group (TDBG) Model Development department is responsible for modelling credit risk in all TDBG retail credit product portfolios (including mortgages, home equity products, indirect auto loans, credit cards, and small business products).

Lieu De Travail: Toronto, Ontario, Canada

Horaire: 37.5

Secteur D’activité: Analyses, informations et intelligence artificielle

Détails De La Rémunération: $76,800 - $115,200 CAD. Ce poste est admissible à une prime de rémunération variable discrétionnaire qui tient compte du rendement de l’entreprise et du rendement individuel.

Job Description: In this position, the individual will be responsible for the development, initial validation, documentation, and support in all stages of audit, implementation and ongoing monitoring of account-level models for credit risk parameters (PD, EAD, and LGD) for all TDBG retail credit product portfolios. The individual will also be responsible for updating/re-developing existing models for these portfolios as required. The predictive models serve as the basis for establishing default, exposure and loss parameter estimates for use in calculating Risk-Weighted Assets (RWA) for TDBG retail credit exposures under the Basel III AIRB approach.

They will also be used to calculate loan loss allowance and economic capital for these portfolios, as well as calculate expected credit losses, RWA, loan loss allowance and economic capital under various macroeconomic scenarios included in the Bank's internal and regulatory stress tests. The position will involve interactions with TDBG Model Validation, Model Risk Management, Internal Audit, and external auditors, as well as with the Bank's Canadian (OSFI) and US (OCC and FED) banking regulators, in order to support their review and approval process for the risk parameter models.

The individual will closely work with and actively support TDBG Retail Risk Management, as well as retail credit product and finance areas by providing a deep analysis of credit risk drivers and parameters under various scenarios for the respective retail credit portfolios. This will entail discussing key observations and conclusions derived from the data analysis and modelling with the various retail credit product, finance, and risk management groups, and assisting these groups in managing product portfolio risk and profitability.

The individual will use leading-edge technologies and develop innovative solutions in the following areas:

• Data mining by making sense of large databases of historical data related to credit risk;
• Predictive credit risk modelling based on rigorous statistical analyses of historical data, regression techniques, and econometric analyses;
• The predictive models leverage both traditional statistical techniques as well as the new AI and machine-learning methodologies; and
• Estimating credit risk embedded in the Bank's US retail credit product portfolios, as well as the amount of regulatory and economic capital the Bank needs to allocate against these portfolios.
• This position provides excellent learning, working and career opportunities in a flexible, highly professional, and motivated team environment, as well as exposure to a variety of high‑paced and intensive modelling projects and a variety of internal and external stakeholders.

• A university degree in Statistics or a related quantitative discipline (Mathematics, Actuarial Science, Computer Science, Econometrics, Operations research);
• Strong working knowledge and hands‑on experience using programming languages such as SAS, SQL, Python, R, MATLAB in the context of data manipulation, data mining, statistical analysis, and predictive modelling;
• Proficiency in creating and manipulating large datasets for data mining and predictive statistical modelling;
• Strong knowledge of modern statistical model development and validation concepts and techniques (particularly linear and logistic regression);
• Strong problem‑solving skills, with the ability to independently identify and solve problems…