Senior Analyst, Quantitative Data Science
$31,200–$31,200 year
On-siteToronto, Ontario, Canada or Montréal, Quebec, Canada
Toronto, Ontario, Canada or Montréal, Quebec, CanadaOn-siteFull Time$31,200–$31,200 yearSenior LevelLarge
Full TimeSenior LevelLarge
Job Summary
Develop and maintain analytical data products for investment workflows by partnering with Portfolio Management, Asset Allocation, and Trading teams to translate financial requirements into scalable data solutions. Manage key quantitative datasets including performance, attribution, holdings, and exposures while ensuring accuracy, validation, and governance. Own the end-to-end lifecycle of analytics products from ingestion through visualization using Power BI and Streamlit, and build cloud-native ETL/ELT pipelines on Google Cloud Platform with dbt and orchestration frameworks. Improve data reliability, automate manual processes, and prepare analytical assets for AI-enabled use cases.
Required Qualifications
- Strong Python development skills and experience building modern data solutions
- Strong understanding of data engineering principles, analytics engineering, data modeling, and best practices
- Experience building scalable ETL/ELT pipelines, analytical data models, and analytics engineering solutions using tools such as dbt
- Experience implementing transformation logic, testing, documentation, lineage, and reusable modeling practices using dbt or comparable analytics engineering frameworks
- Experience with cloud-native platforms such as Google Cloud Platform and BigQuery
- Experience with orchestration frameworks such as Prefect, Dagster, or Airflow
- Familiarity with GitHub, code reviews, CI/CD concepts, Docker, and modern software development practices
- Experience building Power BI solutions, semantic models, and analytical applications
- Understanding of data quality, validation, reconciliation, monitoring, and governance patterns
- Ability to diagnose issues spanning data dependencies, transformation logic, orchestration, and reporting layers
- Solid understanding of investment and financial analytics concepts such as Portfolio management workflows, Performance and attribution analytics, Holdings, positions, exposures, and reference data, Market data and time-series analytics, Risk and exposure analysis, Financial reporting and compliance processes
- Ability to Understand investment workflows and analytical requirements
- Ability to Collaborate effectively with portfolio managers, analysts, quantitative teams, and data engineering partners
- Ability to Translate business and financial requirements into scalable analytical solutions
- Ability to Balance technical excellence with practical investment and operational needs
- Undergraduate or master's degree in Computer Science, Engineering, Mathematics, Finance, Financial Engineering, or a related field
- 5+ years of relevant experience for intermediate candidates; 8+ years for senior candidates
- Experience working at the intersection of finance, analytics, data engineering, and technology
- Experience building data products, analytical solutions, modern reporting capabilities, or production-grade data pipelines
- Experience supporting investment workflows, financial analytics, or quantitative processes
- Demonstrated ability to deliver and support production-grade data and analytics solutions
- High ownership and accountability
- Strong collaboration skills across business, analytics, data engineering, and platform teams
- Product-oriented mindset focused on business outcomes, usability, maintainability, and reuse
- Ability to operate effectively in ambiguous environments and drive initiatives to completion
- Strong problem-solving, analytical thinking, and debugging skills
- Strong communication skills with both technical and non-technical audiences
- Ability to balance short-term delivery requirements with long-term data and platform sustainability
- Focus on quality, reliability, supportability, and continuous improvement
- Advanced proficiency in French, as the candidate will be required to communicate daily with English- and French-speaking clients and partners across Canada via email and phone calls
Desired Qualifications
- Experience working directly with Front Office or investment teams
- Prior exposure to portfolio management, trading, performance, attribution, risk, or investment reporting environments
- Experience designing analytical data products, dbt models, semantic layers, or reusable reporting datasets
- Experience supporting internal analytics platforms, shared data services, or self-service analytics ecosystems
- Familiarity with modern orchestration, containerization, automation, and observability frameworks
- Exposure to cloud-native architectures and scalable analytical application development
- Experience contributing to data governance, data quality automation, or analytical operating standards
- Experience integrating AI capabilities into analytics workflows with appropriate validation, controls, and monitoring
- Familiarity with AI-enabled analytics workflows, enterprise AI capabilities, or AI-ready data product design
- Experience working with financial datasets or investment analytics
- CFA or other financial designations
- CFA, CQF, FRM, or other quantitative or financial designation
- Experience working at the intersection of finance, analytics, data engineering, and technology
- Experience building data products, analytical solutions, modern reporting capabilities, or production-grade data pipelines
- Experience supporting investment workflows, financial analytics, or quantitative processes
- Demonstrated ability to deliver and support production-grade data and analytics solutions
- Curiosity, continuous learning mindset, and interest in applying technology to investment data and processes
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