Senior Analyst, Quant System

iA Financial Group (Industrial Alliance)

Quant Systems Engineer building reusable Python, data pipeline, and AI-enabled solutions for iA Global Asset Management. Partnering with investment teams across Quebec and Ontario to productionize quantitative workflows.

Posted 8/18/2026full-timeQuebec City • 🇨🇦 CanadaSenior💰 CA$70,000 - CA$110,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong Python software engineering skills and experience in building production-grade solutions within data-intensive and quantitative environments. Proficient in developing maintainable software, collaborating with cross-functional teams, and implementing AI-assisted capabilities and data pipelines.

Highest-signal resume keywords

Python Software EngineeringData Pipeline OrchestrationAI-Assisted DevelopmentETL/ELT ProcessesQuantitative Finance Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonData ValidationTime-Series AnalysisQuantitative ModelingDebuggingCI/CD ConceptsOrchestrationContainerizationAutomation FrameworksProduction-Grade Development

Soft Skills

CollaborationCommunicationOwnershipProblem-SolvingAmbiguity Management

Tools & Technologies

GitCloud-Native EnvironmentsAnalytical Data ProductsInternal ToolingShared Engineering Components

Industry Keywords

Quantitative ResearchInvestment TechnologyRisk ManagementPortfolio ManagementFinancial Instruments

Tech Stack

Tools & technologies

CloudETLPython

About the role

Key responsibilities & impact

Partner with Front Office teams including Quantitative Equity, Trading, Risk, and Asset Allocation to co-design and co-develop quantitative solutions
Translate research, investment, and analytical workflows into production-ready implementations
Act as a technical counterpart bridging quantitative intent and platform constraints
Support the full lifecycle of quantitative solutions from design and deployment through ongoing evolution
Standardize and operationalize analytical workflows
Collaborate with data engineering partners on reliable, validated, and orchestrated data pipelines
Identify opportunities for AI-assisted capabilities, automation, and intelligent workflow support
Define, implement, and maintain reusable engineering capabilities, solution patterns, and development standards
Contribute Python packages, libraries, frameworks, documentation, standards, and best practices
Improve analytics and quantitative computing environments across production and non-production environments
Contribute to migrations, upgrades, and platform standardization initiatives
Build tooling, automations, and platform capabilities supporting quantitative workflows
Participate in incident triage, root-cause analysis, deployment, monitoring, troubleshooting, and operational support
Design, build, and support data pipelines connecting source data, transformations, model logic, and downstream reporting or application layers
Contribute to reusable packages, solution templates, orchestration patterns, deployment and monitoring tools, shared components, migration patterns, AI-enhanced workflows, and reusable data pipeline templates

Requirements

What you’ll need

Strong Python software engineering skills and production-grade development practices
Experience designing maintainable, modular, and reusable software solutions
Experience in data-intensive, analytics-heavy, or quantitative environments
Familiarity with cloud-native development environments and shared tooling ecosystems
Working knowledge of Git-based workflows, code reviews, and CI/CD concepts
Experience building internal tools, libraries, automation capabilities, or shared engineering components
Strong debugging and problem-solving across research and production contexts
Ability to diagnose application logic, orchestration, data dependency, and runtime environment issues
Familiarity with modern AI capabilities, AI-assisted development, or applied AI/ML solutions
Experience with ETL/ELT, orchestration, data validation, and data quality patterns
Understanding of time-series analysis, financial instruments, risk concepts, modeling, backtesting, and performance evaluation
Ability to read quantitative logic and translate quantitative requirements into scalable technical solutions
Strong collaboration, communication, ownership, autonomy, and ambiguity-management skills
Undergraduate or master’s degree in Computer Science, Engineering, Mathematics, Finance, Financial Engineering, or a related field preferred
5+ years of relevant experience for intermediate candidates; 8+ years for senior candidates
Experience at the intersection of software engineering, analytics, quantitative research, or investment workflows
Demonstrated ability to build and support production-grade technical solutions
Experience in quantitative finance, investment technology, trading, risk, or portfolio management is an asset
Intermediate proficiency in French, required for daily communication with French-speaking clients and partners across Canada via email and phone
Familiarity with orchestration, containerization, automation frameworks, cloud-native architectures, scalable application development, platform engineering, developer enablement, internal tooling, data pipeline orchestration, data quality automation, analytical data products, and production AI integration

Benefits

Comp & perks

A work environment where learning and development merge with a collective pursuit of excellence
A healthy, safe, fair, and inclusive environment
Hybrid work environment with flexibility and access to inspiring and innovative workspaces
Flexible group insurance
Competitive pension plan
Stock purchase plan
Vacation days
Wellness/personal development days
Telemedicine
Employee and family assistance program
Ergonomic furniture program
Performance bonus
Discounts on iA products