The position at a glance

This role supports BNP Paribas' mission by providing a robust second line of defense through the independent review of artificial intelligence models. The main objective is to manage model risk by ensuring the conceptual soundness and regulatory compliance of AI applications across the organization. By performing effective challenges, the position helps maintain the integrity and reliability of the bank's quantitative frameworks.

In detail

• Conduct independent quantitative reviews of AI models within BNPP CUSO IHC to ensure alignment with internal standards and regulatory guidance such as SR26-2.
• Lead the validation of diverse AI models used by Global Markets and Global Banking teams by leveraging technical expertise to support various business units.
• Challenge the conceptual soundness and implementation of models to ensure they remain fit-for-use and produce reasonable outputs.
• Collaborate with validation managers to develop appropriate validation plans that provide an effective challenge commensurate with identified model risk levels.
• Partner with data science teams within BNPP CIB to facilitate compliance with established model validation regulatory requirements.
• Produce high-quality technical documentation of the effective challenge process to support committee reviews and informed decision-making.
• Assess ongoing model performance through continuous monitoring to ensure sustained accuracy and reliability.
• Defend technical conclusions to management to provide clarity on model risks and validation outcomes.

The strengths and skills that will help you succeed

While the description belowdescribes our ideal candidate, we encourage applicants to apply even if they do not fully meet the complete list of qualifications noted

• Master or PhD in Finance, Economics, Statistics, Computer Science, Data science or any other related quantitative field.
• The knowledge of English is required.*
• Minimum 3 years of experience validating or developing models related to quantitative research in finance or real-world machine learning projects.
• Solid quantitative, statistical, and traditional AI knowledge for performing predictive modeling, time series analysis, and statistical inference.
• Programming proficiency in Python or R to execute mathematical and statistical computations.
• Machine learning framework expertise, including LightGBM, Tensorflow, or PyTorch, to evaluate complex model architectures.
• Generative AI framework experience, such as LangChain or LangGraph, to assess emerging AI technologies.
• NLP framework familiarity, including NLTK, spaCy, or Gensim, for reviewing text-based modeling.
• Regulatory knowledge of SR26-2 or SR11-7 to ensure all validations meet industry compliance standards.
• Agentic AI system familiarity to support the evaluation of evolving autonomous agent technologies.
• Trading product and strategy familiarity to provide context-specific validation for Global Markets.
• Technical writing skills to produce clear and high-quality documentation for internal stakeholders.
• Collaborative communication and synthesis skills when presenting complex findings to management and cross-functional teams.

*Given the vast majority of our clients, both internal and external, are based outside of Quebec and Canada, specific language requirements may apply. Professional working proficiency in English language is required.

What's in it for you

Alongside a competitive compensation, we provide a comprehensive suite of flexible benefits designed to support your health, wellbeing, and long-term success:

Health & Wellness A menu of flexible options for you and your family, including a 24/7 telemedicine service.

Mental-Health Support Up to $5,000 per year for sessions with mental-health practitioners, plus unlimited access through our Employee Assistance Program.

Financial Benefits A defined-contribution pension plan and a range of additional financial perks.

Paid Volunteering Days Take time off to give back to the community.

Learning & Development Access to high-quality training, personal-development programs, and clear pathways for internal career progression across our global organization.

Work-place flexibility - Hybrid work is available for most roles. You'll be required in the office at least three days per week, with one of those days being either a Monday or a Friday.

To find out more about our range of benefits, click hre