Our client in Toronto is looking for a Risk Consultant to join a multi-disciplinary group to support Cloud-based Risk services.
Working from an existing platform, Consultants assist in the design, building, and maintenance of a dynamic and flexible Cloud based risk service.
The team works collaboratively and members are encouraged to explore and develop unique ways to solve challenges. Projects require individuals who are able to research and experiment to develop new ideas and solutions.
Working with an open and constructive mindset, guidance and feedback is available from the broader group.
Provide subject matter expert advice to internal and external audience for risk management topics including product valuation methods, scenario based risk analysis and portfolio risk reporting standards.
Own functional projects related to feature extensions including interaction with development team (team & core), research and client service teams.
Involves independent scope setting, task determination, priority setting and development support.
Consulting with sales and pre-sales to present Service capabilities to prospects. Identify and fill gaps where necessary.
Investigation of data sourcing, transformation and storage for use in the risk management process. May involve extensive communication and negotiation with external vendors.
Investigation and remediation of client support issues (3rd level support).
Work with the Development team to improve the core software offering.
University Degree in the field of Economics, Finance, Mathematics, Statistics or other quantitative discipline. Must have theoretical understanding of financial economics, mathematics and statistics, and practical knowledge of financial markets and risk management standards.
Advanced Degree in Financial Engineering or Mathematical Finance is beneficial; CFA, PRM or FRM designation(s) beneficial.
Must have excellent communication skills, both verbal and written.
Must have presentation presence and experience - able to convey complex ideas to a functional and technical audience.
Minimum 5 years of relevant experience in the financial industry working with front or middle office portfolio risk management systems;
must have experience with financial market data interfaces such as Reuters, Bloomberg or ICE.
Experience in an advanced technical environment collaborating on or writing scripts or code, integration, testing and deployment;
familiarity with data science languages such as R or Python, as well as other technical skills / aptitude including use of networks, Linux operating system and client / server applications.
Practical knowledge and experience around financial instrument valuation methods and (stochastic) scenario generation techniques.
Strong research and problem solving skills.