Applications Programmer II - 55085

S I Systems; Toronto; Hybrid; CAD 80,000 - 120,000; Full time

Job summary

An established industry player is seeking a Modelling/Forecasting Analyst to join their innovative NRMD group. This role involves developing and enhancing credit risk models for non-retail portfolios, utilizing advanced statistical modeling techniques. You will design econometric models, conduct applied research, and collaborate with cross-functional teams to drive impactful projects. If you have a strong theoretical background and programming skills in SAS, Python, or MATLAB, this opportunity offers a dynamic work environment with a hybrid model that encourages collaboration and growth.

Qualifications

• Strong background in data-driven statistical modeling and algorithms.
• Programming experience in SAS, Python or MATLAB is preferred.
• Experience with relational databases and SQL.

Responsibilities

• Develop and enhance credit risk models for non-retail portfolios.
• Design econometric models to explore credit losses and macroeconomic relationships.
• Collaborate with teams and participate in cross-functional projects.

Skills

Statistical Modeling

Supervised Learning

Unsupervised Learning

Discriminative Models

SAS

Python

MATLAB

SQL

Education

Graduate degree in Applied Econometrics

Graduate degree in Economics

Graduate degree in Mathematics

Graduate degree in Statistics

Graduate degree in Actuarial Science

Graduate degree in Computer Science

Graduate degree in Physics

Job description

Work Location: Hybrid Toronto – (ANY 2 days a week)

CANDIDATE PROFILE DETAILS:

% Interaction with Stakeholders: 25%

Team Size: 9

SUMMARY OF DAY-TO-DAY RESPONSIBILITIES:

The NRMD group is hiring a Modelling/Forecasting Analyst to develop, enhance, and implement credit risk models for non-retail portfolios. Detailed responsibilities are as follows:

• Develop PD, LGD and UGD models for DFAST, EWST, CECL and IFRS9 usage;

• Design econometric models to explore relationships between credit losses and the macroeconomic environment;

• Design mathematical and statistical algorithms to enhance existing models;

• Conduct applied research for credit risk modeling;

• Perform ad hoc analyses as required by management and other business partners;

• Participate in design, planning, implementation and testing of various modeling initiatives;

• Collaborate with non-retail teams and participate in cross-functional projects as needed;

• Produce and maintain well-articulated documentation on above;

• Write and maintain robust code for performing the above functions.

MUST HAVE:

Strong background in data-driven statistical modeling, supervised learning, unsupervised learning and discriminative models.

Strong theoretical and numerical background.

• Programming experience in SAS, Python or MATLAB is strongly preferred.

• Knowledge of coding standards and object-oriented programming.

• Experience working with relational databases and SQL.

EDUCATION

•Graduate degree in a quantitative field, such as Applied Econometrics, Economics, Mathematics, Statistics, Actuarial Science, Computer Science or Physics.