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Ai In Finance Jobs in Quebec (NOW HIRING)

Top Aces, Inc.

BI & AI Analyst

Dorval, QC

Experience in aviation, MRO, engineering, operations, finance, inventory management, supply chain ... Exposure to AI opportunity identification, forecasting, optimization, automation, anomaly detection ...

Jay Analytix

AI Engineer - Banking Domain

Montreal, QC · On-site

MUST-HAVE * 7+ years in AI/ML engineering, with 3+ years in banking or financial services. * Advanced Python skills: PyTorch/TensorFlow, Scikit-learn, Pandas. * Hands-on MLOps experience: MLflow ...

TailorCare

Data Platform Architect

Montreal, QC · Hybrid

... financial investment) and Muscle (operational intensity). This requires a data and AI platform that ingests, resolves, scores, decides, and acts in minutes, with the explainability and governance ...

Broccolini

Senior AI Skill builder

Kirkland, QC · On-site

... les finances, les ressources humaines, l'estimation, la gestion de projets et les operations. Il ... Interested in understanding how teams actually operate and how AI can improve execution in ...

Bounteous

Database Developer

Montreal, QC · On-site

Bounteous is a global AI Services firm where agentic engineering and human experience converge to ... Experience in finance domain * Exposure to CI/CD tools Information Security Responsibilities

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Ai In Finance information

What is the difference between Ai In Finance vs Data Analyst in Finance?

AspectAi In FinanceData Analyst in Finance
Required CredentialsDegree in Finance, Computer Science, or related fields; knowledge of AI and machine learningDegree in Finance, Statistics, or related fields; proficiency in data analysis tools
Work EnvironmentTech-driven finance teams, AI development labs, financial institutionsFinancial firms, banks, investment companies, data analysis departments
Employer & Industry UsageFinancial technology companies, banks integrating AI solutionsFinancial services firms analyzing market data, risk, and client information

Ai In Finance focuses on developing and implementing AI solutions within finance, requiring technical and financial expertise. Data Analysts in Finance interpret financial data to support decision-making. While both roles work with financial data, Ai In Finance emphasizes AI development, whereas Data Analysts focus on data interpretation and reporting.

How do professionals in AI in finance typically collaborate with other departments within a financial institution?

Professionals working in AI in Finance often collaborate closely with teams such as risk management, compliance, and data engineering. They work together to define business requirements, ensure the quality and security of financial data, and interpret AI models’ results for practical decision-making. Effective communication is key, as AI specialists must translate complex technical findings into actionable insights for non-technical stakeholders. This collaborative environment fosters innovation and helps drive solutions that align with both regulatory standards and business goals.

What is AI in finance?

AI in finance refers to the use of artificial intelligence technologies and machine learning algorithms to automate, enhance, and optimize various financial services and processes. This includes applications such as fraud detection, algorithmic trading, credit risk assessment, customer service chatbots, and personalized financial advice. By leveraging large datasets and advanced analytics, AI can improve decision-making, reduce operational costs, and deliver more accurate and timely financial insights. Many financial institutions are increasingly adopting AI to stay competitive and comply with regulatory requirements.

What are the key skills and qualifications needed to thrive as an AI professional in finance?

To thrive as an AI professional in Finance, you need a strong background in data science, machine learning, quantitative analysis, and finance, often supported by degrees in computer science, mathematics, or finance. Familiarity with programming languages like Python or R, experience with AI/ML frameworks (such as TensorFlow or PyTorch), and understanding of financial systems or regulatory standards are typically required. Strong analytical thinking, attention to detail, and effective communication skills set top performers apart in this field. These skills are vital for developing robust AI solutions that drive financial insights, improve decision-making, and ensure regulatory compliance.
What are popular job titles related to Ai In Finance jobs in Quebec? For Ai In Finance jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Ai In Finance jobs in Quebec look for? The top searched job categories for Ai In Finance jobs in Quebec are:
Ai In Finance jobs near you
Infographic showing various Ai In Finance job openings in Quebec as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution.

Application Support Analyst (AI-Enabled | BA & Development Hybrid)

Societe Generale

Montreal, QC • On-site

Other

Re-posted 14 days ago

Job description

We are looking for an Application Support Analyst who brings a balanced mix of production support, business analysis, and technical development skills, enhanced by the use of AI tools and automation techniques.
In this role, you will ensure the stability of business-critical applications while actively contributing to continuous improvement, automation, and solution design. You will collaborate closely with business stakeholders and development teams, occasionally functioning as a Business Analyst or Developer depending on project needs.
Key Responsibilities
Production Support & Operations
    Monitor daily batch jobs and application processes, ensuring smooth execution.
    Provide Level 1, 2, and 3 support, troubleshooting incidents and resolving issues efficiently.
    Conduct root cause analysis (RCA) and implement preventive solutions.
    Prioritize incidents based on business impact and urgency.
    Participate in on-call rotations, maintenance windows, and support during infrastructure activities.
    Maintain a stable production environment with minimal disruption.
AI & Automation Enablement
    Use AI tools (e.g., Copilot) to improve efficiency in debugging, log analysis, and documentation.
    Apply prompt engineering techniques to accelerate daily operational tasks.
    Identify and implement opportunities for automation of repetitive processes.
    Enhance monitoring systems with intelligent alerts and automated responses.
Business Analysis Responsibilities
    Work with stakeholders to gather and translate business requirements into technical solutions.
    Analyze incidents and user needs to identify functional improvements.
    Create and maintain: 
o    User stories
o    Functional documentation
o    Acceptance criteria
    Participate in Agile ceremonies and contribute to backlog refinement.
    Act as a liaison between business and technical teams, ensuring clear communication and expectations.
________________________________________
Development & Technical Contributions
    Develop and maintain scripts using Python, PowerShell, Unix Shell, or Batch to automate processes.
    Read, analyze, and troubleshoot Java or .NET application code when needed.
    Work with APIs to: 
o    Integrate systems
o    Build lightweight tools or utilities
    Contribute to minor enhancements, bug fixes, and technical improvements.
DevOps & Release Support
    Execute deployments and support change management processes.
    Work with CI/CD pipelines such as Jenkins, GitHub Actions, or similar tools.
    Perform QA testing for new features and releases.
    Participate in infrastructure tasks including: 
o    Upgrades and patching
o    Disaster recovery testing
Monitoring & Tools
    Use monitoring and scheduling tools such as: 
o    Elastic Stack (ELK), Grafana
o    Autosys / UC4
    Improve system observability by building dashboards and alerts.
    Continuously enhance application monitoring and operational controls.
Collaboration & Communication
    Collaborate with global teams across Canada, the US, Paris, and Bangalore.
    Handle user requests efficiently while maintaining clear communication.
    Provide timely updates and manage stakeholder expectations effectively.
 

Required Skills
    Strong scripting skills: Python, PowerShell, Unix Shell, Batch
    Solid knowledge of SQL and relational databases
    Experience with monitoring tools (Grafana, ELK) and schedulers (Autosys, UC4)
    Experience with CI/CD tools (Jenkins, GitHub Actions, TeamCity, etc.)
    Familiarity with AI tools and prompt engineering concepts
    Experience in Agile environments
    Ability to manage multiple priorities effectively
    Experience with production support and on-call rotation
Preferred Qualifications
    Experience in financial services
    Knowledge of Azure and/or AWS cloud platforms
    Experience with enterprise application troubleshooting (Java/.NET)
    ITIL certification
    Exposure to automation, AIOps, or AI-driven operational tools
Role Value
This position is ideal for professionals who want to go beyond traditional support and:
    Work across Support, Business Analysis, and Development
    Leverage AI to increase efficiency and innovation
    Contribute to automation and modern DevOps practices
    Grow into roles like SRE, Technical Analyst, or AI-enabled Engineer

LANGUAGE: 

Ability to communicate in English, both orally and in writing, is a requirement as the person in this position will need to collaborate regularly with colleagues and partners in the United States. 

Due to US Federal Securities law that may apply to this position, candidates who will apply for this position may be required to submit to an enhanced background screening, including the collection of their fingerprints by a third-party vendor selected by the Financial Industry Regulatory Authority ("FINRA").

Apply