Software Engineer with Risk Modelling

4 weeks ago


Toronto ON, Canada Nexus Systems Group Inc. Full time

Software Developer - Quantitative models/optimization
As part of the development team, the individual will be involved with every aspect of production software development cycle, process automation, and creation of front-end interactive web-based tools and apps for traders/analysts.
- The incumbent will be required to provide technical leadership and support technical deployment within the team, provide insights on optimal technology strategies, designing efficient and robust solutions, and creating new interfaces and tools that focus on continually improving the customer experience
- the candidate will be responsible for reviewing the requirements from other Treasury stakeholders and translating use cases into production-quality analytical tools.
-Develop, implement, and deploy analytical solutions, software tools, and production systems to support Treasury's hedging, analytics, and forecasting.
-Focusing on the development of user interfaces, front-end applications, and mid-level API development.
• Develop and deploy analytical tools for risk exposure, margin analysis, and stress testing.
• Collaborate with stakeholders for agile product releases.
• Analyze balance sheet exposures and perform scenario testing.
• Work closely with market-facing, risk management, and finance teams.
• Communicate technical concepts to a wide range of stakeholders.
• Have advanced experience in programming, database management, machine learning, and analytics.
• This role requires a strong technical background, analytical skills, and the ability to collaborate in a fast-paced environment to develop and deploy financial analytics tools.
1)5+ years of Experience in software development for quantitative models and optimization (Python)
2)5+ years of Expertise in programming languages, data management (ETL)
4) 3+ years of experience working in development teams utilizing project management tools such as JIRA, Confluence, and Source control (GIT)
2) software development for machine learning
3) Working knowledge of cloud architectural patterns (eg. 4) Knowledge of financial accounting, interest rate markets, and regulatory requirements
5) Masters degree in Quantitative field
degree in a quantitative field (Science, Computer Science, Engineering etc.)
The ideal candidate will have prior work experience within the field of quantitative finance. #


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