Quantitative Analyst

Permanent contract|Montreal|Risks

Quantitative Analyst

Montreal, Canada Permanent contract Risks


The Quantitative Advisor will execute independent review of business models under both US and Canada regulations working closely with cross functional teams, including business stakeholders, model developer, model validators (Paris and NY office), IT, auditors. Presentation of validation analysis to senior management is in the scope of this role. He/she will be exposed to a variety of models used by the business and support functions, including models for credit risk, market risk, counterparty risk, stress testing, margining, IFRS9, trading algorithms and financial crime compliance.

In collaboration with Senior Quantitative Advisors and the team Manager, the JQuantitative Advisor will:

  • Conduct independent model review of relevant models that are employed in SG Americas at all stages of their lifecycle by:
    • Assessing model conceptual soundness to ensure the consistency of model design by performing quantitative analyses and statistical tests, developing challenger models for benchmark, reviewing model development processes, and challenging the theoretical aspects considering published research and industry practice;
    • Working with large, complex datasets to verify data input quality and processing (feeding, transformation), model output accuracy, and employ advanced statistical techniques to work with sparse datasets;
    • Assessing data quality and consistency between data characteristics and modeling assumptions;
    • Replicating and review model architecture to verify the computation accuracy of a model and ensure the model is implemented as designed and all model components are functioning as intended
    • Analyzing model output through backtesting, benchmarking, sensitivity analysis by using quantitative tools and techniques;
    • Assessing the model use to ensure it is aligned with the intended purpose by identifying and reviewing model output production, usage, reporting, and business processes;
    • Reviewing model ongoing monitoring to ensure that model is performing as intended by evaluating whether changes in products, exposures, activities, clients, or market conditions necessitate adjustment, redevelopment, or replacement of the model. Verify the model performance over time and ensure that model limitations are assessed;
    • Conducting and interpreting 2LOD model monitoring;
    • Assessing model governance aspects such as model change management, ongoing monitoring, and model risk assessment;
  • Evaluate overall model risk, report findings and propose recommendations of remediation. Draft comprehensive validation documents and prepare model review materials for MRM management and committees, RISQ management, and model and business partners; 
  • Maintain positive relationships and continuous communication with model and business stakeholders;
  • Candidate must be able to communicate model review outcomes (and intermediate feedback) verbally – not only in validation report (mentioned above);
  • Work with front office, model developers and risk managers with day-to-day model review and remediation follow-up.

Profile required

Requirements for the Quantitative Advisor:

  • Minimum of a Bachelors Degree (Master and PhD preferred) in a quantitative area: Mathematical Finance, Financial Engineering, Statistics, Economics, Computer Science, Technology, Engineering and Mathematics;
  • 3 years of experience in Model Development or Validation in finance/risk management, or Front Office Quant role. Fewer years of relevant experience will be considered for candidates with a PhD degree;
  • Excellent quantitative programming skills in at least one programming language (e.g. Python, R, C++, SAS, Matlab);
  • Advanced knowledge of statistics, econometrics, machine learning;
  • Strong verbal and written communication skills with the ability to work with quant or non-quant staffs;
  • Awareness of model risk management and associated regulatory requirements;
  • Team-oriented with a keen sense of ownership and accountability;
  • Project and time management skills to work in a multi-tasking working environment;
  • Experience with various quantitative models in areas of Market Risk, Credit Risk, Operational Risk and PPNR is a plus;
  • Experience in large data management and quantitative analysis is a plus;
  • Bilingual (English and French) is a plus;
  • FRM or other Risk Management certifications is a plus;
  • PhD is a plus.

Business insight

Société Générale (SG) is multinational banking and financial services company providing services worldwide in 67 countries. Founded in 1864 and headquartered in Paris, SG is France’s third largest bank by total assets. As a global bank, SG core businesses cover Retail Banking in France (Société Générale), International Banking and Financial Services (IBFS), and Corporate and Investment Banking (SG CIB). SG group reported 2017 operating income of € 4.76 billion, total assets € 1.27 trillion. Team spirit, Innovation, Responsibility, and Commitment – the values upon which SG was founded – have guided the company’s actions for over 150 years.

Conformément son engagement à fournir un milieu de travail sécuritaire pour toute personne accédant à ses installations, à compter du 15 novembre 2021, en vertu de la politique de vaccination contre la Covid-19 Société Générale Canada, seuls les employés pleinement vaccinés seront autorisés à venir au bureau de Montréal et de Toronto

In accordance with its commitment to provide a safe work environment for anyone accessing its facilities, as of November 15, 2021, under Societe Generale Canada's Covid-19 vaccination policy, only fully vaccinated employees will be allowed to come to the Montreal and Toronto offices.

We are an equal opportunities employer and we are proud to make diversity a strength for our company. Societe Generale is committed to recognizing and promoting all talents, regardless of their beliefs, age, disability, parental status, ethnic origin, nationality, gender identity, sexual orientation, membership of a political, religious, trade union or minority organisation, or any other characteristic that could be subject to discrimination.

Reference: 21000ZPW
Starting date: immediate
Publication date: 2022/11/11