Senior Analyst, Quant System

Jobtailor

Quebec

On-site

CAD 110,000 - 150,000

Full time

2 days ago

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Job summary

Jobtailor in Canada is seeking an experienced Quantitative Software Engineer to design and implement production-grade quantitative solutions with Python. You will partner with Front Office teams, translate research into deployable code, and help standardize data pipelines and analytics environments.

Strong emphasis on CI/CD, cloud-native stacks, and AI-assisted workflows. The role requires 5+ years for intermediate candidates or 8+ years for senior candidates, with fluency in French for daily

Qualifications

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 read quantitative logic and translate quantitative requirements into scalable technical solutions.
Intermediate proficiency in French, required for daily communication with French-speaking clients and partners across Canada via email and phone.

Responsibilities

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

Skills

Python

Data pipelines

CI/CD

Orchestration

AI-assisted development

Problem-solving

Education

Bachelor's or Master's in Computer Science, Engineering, Mathematics, Finance, Financial Engineering, or related field

Tools

Git

Containerization

Cloud-Native Environments

Automation Frameworks

Job description

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

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

Core Competencies

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.

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