Title:  Associate, Global Analytics & Financial Engineering - Toronto

Requisition ID: 201176

Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

Who are we?

Global Analytics and Financial Engineering is a critical function within the Bank’s Global Banking and Markets (GBM) division. The derivatives valuation models and analytics developed by the team are used globally for pricing, hedging, risk management, trading limits and capital. The accuracy and the performance of these models have a direct impact on GBM’s competitiveness and profitability. The reliability and the robustness of the analytics enable the business to view and manage risks efficiently.

What’s in it for you?

• Work with leadership during your potential rotational areas covering equity, rates, credit, commodity, and foreign exchange.
• Champions a customer focused culture to deepen client relationships and leverage broader Bank relationships, systems and knowledge.
• Collaborate with senior members to learn about derivatives products, valuation models, and the model development technology stacks.
• Contribute to the derivatives valuation model development life cycle from business requirements gathering, model research and selection, coding and testing, and the final deployment.
• Participate in the development and support of front office analytics used for pricing, hedging, and risk management.
• Provide subject matter expertise to our model and analytics stakeholders such as trading and sales, risk management teams, and technology groups.
• Apply the Bank’s risk appetite and risk culture in day-to-day activities and decisions.

Do you have the skills that will enable you to succeed in this role?

We’d love to work with you if you have: 

•  Doctorate or Master’s Degree in quantitative finance, mathematics, computer science, physics, or other quantitative areas.
•  Up to 2 years’ experience after graduation with a passion for quantitative finance.
• Demonstrable knowledge of numerical methods and computational modelling: for example, finite difference / finite element, Monte Carlo simulation, optimization, artificial intelligence.
• Strong programming skills in C++ or Python and the willingness to learn other programming languages.
• Good communication and interpersonal skills and a team player and ability to work well in a fast-paced environment with changing priorities.
• Solutions-focused Attitude, recognizing Opportunities to not only learn but to contribute to team outcomes, and showing Ownership over delivery.
• Knowledge of reinforcement learning or deep learning is considered an asset.

Working Arrangement:

• This position is currently an on-site role, with the expectation that you will work 3-5 days a week in the office. Please note that this is subject to change based on the needs of the business.

Location(s):  Canada : Ontario : Toronto 

Scotiabank is a leading bank in the Americas. Guided by our purpose: "for every future", we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.  

At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know. If you require technical assistance, please click here. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.

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