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Model Risk Management Jobs in Quebec (NOW HIRING)

Role Overview Risk management at this company is not a brake on growth -- it is the engine that ... Demonstrated proficiency with Python/R modeling frameworks: Sklearn, XGBoost, LightGBM. * Mandarin ...

These could include Appointed Actuary work, model development, model validation, pricing and product development, model risk management, climate risk management, etc. * Participate in business ...

The Enterprise Risk Management department in the RISQ Division oversees risk management for SG ... Contribute to the development and enhancement of the ERM "conceptual data model" (connections ...

These could include Appointed Actuary work, model development, model validation, pricing and product development, model risk management, climate risk management, etc. * Participate in business ...

Familiarity with model validation, model risk management, governance, or audit processes. Experience evaluating vendor-provided analytical solutions, AI platforms, or commercial Generative AI ...

... or in model risk management within the financial or professional services sectors, as well as with relevant banking, securities, or insurance regulatory agencies. * Experience in professional ...

... or in model risk management within the financial or professional services sectors, as well as with relevant banking, securities, or insurance regulatory agencies. * Experience in professional ...

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Model Risk Management information

See Quebec salary details

$24K

$121.1K

$244K

How much do model risk management jobs pay per year?

As of Sep 13, 2026, the average yearly pay for model risk management in Quebec is $121,104.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,500.00 and $151,500.00 per year, depending on experience, location, and employer.

What is a model risk management?

A Model Risk Management (MRM) job involves identifying, assessing, and mitigating risks associated with financial and analytical models used by an organization. Professionals in this role ensure models are accurate, reliable, and comply with regulatory requirements by conducting validation, testing, and performance monitoring. They work closely with model developers, risk teams, and auditors to manage model lifecycle processes. Strong quantitative, analytical, and regulatory knowledge are key skills for success in this field.

What are some common challenges faced by professionals in model risk management roles?

Professionals in Model Risk Management commonly encounter challenges such as evolving regulatory requirements, the complexity of advanced financial models, and ensuring effective communication between technical and non-technical stakeholders. Staying current with industry best practices while rigorously validating and documenting models can be demanding but is critical for reducing financial and operational risks. Team members often work cross-functionally, collaborating closely with quants, risk managers, and IT teams to evaluate model performance and implement improvements. Adapting to new analytical tools and maintaining a proactive approach to emerging risks will help you succeed and grow in this dynamic field.

What are the key skills and qualifications needed to thrive in model risk management, and why are they important?

To excel in Model Risk Management, a professional needs a strong grounding in quantitative finance, statistics, and risk assessment, often backed by advanced degrees in relevant fields. Familiarity with technical tools such as Python, R, SAS, and model validation platforms, along with relevant certifications like FRM or CFA, is highly beneficial. Exceptional communication skills, attention to detail, and critical thinking help individuals stand out when interacting with model developers and risk committees. Mastery of these abilities ensures thorough risk analysis, regulatory compliance, and effective mitigation of financial model risks within the organization.

What does a model risk management do?

A model risk management professional oversees the identification, assessment, and mitigation of risks associated with financial and operational models. They ensure models are accurate, reliable, and compliant with regulations, often using validation tools and statistical analysis. This role helps prevent financial loss and supports decision-making processes within organizations.

What are popular job titles related to Model Risk Management jobs in Quebec?

For Model Risk Management jobs in Quebec, the most frequently searched job titles are:

What job categories do people searching Model Risk Management jobs in Quebec look for?

The top searched job categories for Model Risk Management jobs in Quebec are:

Infographic showing various Model Risk Management job openings in Quebec as of September 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $121,104 per year, or $58.2 per hour.

Lead Risk Manager, Payment Fraud

Montreal, QC • Hybrid

$150K - $180K/yr

Full-time

Re-posted 8 days ago


Job description

Lead Risk Manager, Payment Fraud

Toronto Onsite  |  Full-Time  |  Hybrid after onboarding  |  Reports to CEO  |  LMIA / PNP sponsorship available

About the Client

Our client is one of Canada's fastest-growing fintech platforms, transforming how consumers pay, save, and earn rewards through a single seamless app. The company processes over USD $100M in annual transaction volume (TPV) with a base of 250,000+ users across North America, and its proprietary, fully in-house technology stack supports 500+ leading retail and brand partners. Headquartered in the Greater Toronto Area with a growing presence in Silicon Valley, the company is currently scaling at 300% year-over-year and is expanding its financial product suite into new categories.

Role Overview

Risk management at this company is not a brake on growth — it is the engine that powers it. The Lead Risk Manager will own end-to-end fraud and payment risk strategy across a multi-currency, cross-border consumer payments ecosystem, building AI-driven detection systems that automate over 90% of fraud interception and free the team from manual review cycles.

This is a builder role for a Risk Leader with hacker instincts and raw analytical horsepower — someone who can reverse-engineer fraud loops, write production-grade SQL and Python, and deploy ML models (XGBoost, LightGBM) into live risk systems. The role reports directly to the CEO and operates as the strategic liaison to global payment processors and vendors.

Key Responsibilities

•     Define the rules, don't just follow them — Lead end-to-end financial risk strategies, from opportunity identification through design, testing, and post-production monitoring.

•     Build AI-driven defense — Develop user behaviour scoring, anomaly detection, and automated interception models using Python/Sklearn/XGBoost/LightGBM, and deploy them into the production risk stack.

•     Counter-strike fraud — Investigate anomalous activity in real time, perform root-cause analysis on chargebacks, and produce authoritative reports on emerging fraud trends across multi-currency and e-commerce flows.

•     Own the data layer — Independently query large datasets in SQL to surface fraud patterns, evaluate model performance, and inform strategy adjustments.

•     Strategic liaison — Act as the single point of contact between the company and external payment processors, card networks, and risk vendors, ensuring alignment on risk policy and incident response.

•     Set the standard — Establish the company's long-term risk operating framework as the platform scales TPV and enters new markets.

Must-Have Requirements

•     5+ years of professional experience, with a minimum of 3 years dedicated to fraud risk and at least 1 year specifically within the payments industry.

•     Hands-on experience identifying and defending against fraud across multi-currency, cross-border, and e-commerce payment environments.

•     Strong reverse-engineering and problem-solving instincts — able to anticipate attacks from a fraudster's perspective.

•     Expert-level SQL for independent querying of large transactional datasets; strong Python proficiency.

•     3+ years of hands-on experience building fraud detection models — feature engineering, training, evaluation, and production deployment.

•     Demonstrated proficiency with Python/R modeling frameworks: Sklearn, XGBoost, LightGBM.

•     Mandarin Chinese fluency (the company operates a bilingual EN/CN working environment; this is a hard requirement).

•     Based in or willing to relocate to the Greater Toronto Area for the onsite onboarding period.

Nice to Have

•     Prior experience at a top-tier payment processor, card network, or fintech with cross-border exposure.

•     Experience leading or mentoring a small risk / data team.

•     Familiarity with North American AML/KYC and consumer payment compliance frameworks.

Compensation & Logistics

•     Base Salary: CAD 150K to 180k

•     Bonus: Risk control performance bonus tied to fraud loss reduction and model deployment milestones.

•     Work Model: Hybrid in Toronto, with a paid 1–2 month onsite onboarding period at the Etobicoke office.

•     Reporting Line: Direct report to the CEO.

•     Immigration Support: Full LMIA and PNP employer sponsorship for top-tier candidates, including all associated costs.

•     Team: Work alongside payment industry veterans and a Harvard-affiliated founder defining the future of AI-driven financial security.

Why This Role

This is not a maintenance seat at a stagnant company. It is a builder seat at a Canadian fintech in hyper-growth, with direct CEO access, a real budget for AI tooling, and the autonomy to define the risk operating model from the ground up. For a senior risk professional who wants to operate as a general rather than an analyst, this is one of the most consequential fraud roles open in the Canadian market today.