Senior Analyst, Treasury Modelling

Build programmed solutions and processes based on requirements from the Treasury and Capital Markets team.

Automate existing spreadsheet-based analysis and to replicate results from other platforms.

Efforts will focus on funds transfer pricing models/ margin reporting, hedge accounting report, duration calculation, liquidity matching, stress testing, liquidity regulatory reporting etc.

The incumbent will ensure all processes are documented as per the Bank documentation standards.

The position supports and provides analytical support to Treasury team members (Liquidity, IRR, etc.) with (customer) behavioral analysis of various asset and liability products.

Review existing behavioural analysis and enhance analysis where beneficial (i.e. initial focus is most highly sensitive assumptions). Streamline analysis processes.

Develop new behavioural analysis as required. Requires the review of existing data and expanding where needed. Requires understanding of result sensitivity to assumptions and of drivers of customer behaviour.

Document all analysis methods and present analysis for approval by Senior Management (i.e. ALCO). Integrate assumptions into IRR/liquidity modeling.

Platform expected to be used are SQL and Python.

Support other Treasury, Finance and corporate requests. This includes the following:

Support Treasury function with additional development. Provide reports for ALCO and ERM meetings. This includes liquidity or interest rate analysis as required (product volume, yields, spreads, option costs).

Support accounting, capital markets and investor relation functions with required analysis and reporting.

Provide support as a subject matter expert on programing / coding.

Ensure all models, processes, and associated controls are documented.

Assist in Model Validation process for new and existing models.

Perform regular performance monitoring as per model requirements

Undergraduate degree with a focus on math and/or computer science.

3 to 5 years of experience in financial model programming.

Strong programming experience and database management knowledge using SQL and Python are needed.

Strong skills in problem solving, logical thinking, process building and analytics.

Awareness of machine learning (including deep learning) and underlying models (LSTM, convolution, deep and shallow layers)

Keen interest in financial markets and financial engineering, strong desire and ability to learn new financial concepts.

Demonstrated understanding in fixed-income financial concepts (i.e. bonds, mortgages, derivatives and yield curves) is an asset.

Knowledge of Liquidity risk, Interest rate risk and hedge accounting will be helpful.

Ability to collaborate with various functional support groups.

Excellent interpersonal and communication skills both written and verbal.

Ability to pay attention to details.

Possess good business acumen.