Senior Analyst, Quantitative Data Science

• Partner with Portfolio Management, Asset Allocation, Trading, Performance, Risk, Research, and other investment teams
• Develop and maintain analytical data products supporting investment workflows
• Translate financial and analytical requirements into scalable data solutions
• Manage performance, attribution, time-series, holdings, positions, exposures, and aggregated analytics datasets
• Ensure investment datasets are accurate, validated, timely, and well-governed
• Own analytical product lifecycles from data ingestion and transformation through delivery and continuous evolution
• Define requirements, priorities, operating expectations, and success measures with stakeholders
• Design scalable data models and transformation pipelines
• Develop Power BI and Streamlit analytical experiences
• Build and maintain ETL/ELT pipelines for investment processes and recurring analytical workflows
• Implement data quality controls, reconciliation, monitoring, and operational runbooks
• Contribute reusable dbt models, standards, templates, documentation, lineage, and semantic-layer components
• Support cloud-native platform modernization and AI-enabled analytical workflows
• Diagnose issues across data dependencies, transformation logic, orchestration, and reporting layers

Requirements

• Strong Python development skills
• Strong understanding of data engineering, analytics engineering, data modeling, and best practices
• Experience building scalable ETL/ELT pipelines and analytical data models using dbt or comparable frameworks
• Experience with transformation logic, testing, documentation, lineage, and reusable modeling practices
• Experience with Google Cloud Platform and BigQuery
• Experience with 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
• Solid understanding of investment and financial analytics concepts
• Ability to understand investment workflows and translate business and financial requirements into scalable solutions
• Experience working with financial datasets or investment analytics is highly desirable
• 5+ years of relevant experience for intermediate candidates; 8+ years for senior candidates
• Experience at the intersection of finance, analytics, data engineering, and technology
• Experience building data products, analytical solutions, modern reporting capabilities, or production-grade data pipelines
• Demonstrated ability to deliver and support production-grade data and analytics solutions
• Advanced proficiency in French; daily communication with English- and French-speaking clients and partners across Canada via email and phone calls
• Undergraduate or master’s degree in a relevant field preferred, not required

Core Competencies

Demonstrates expertise in developing and maintaining analytical data products, building scalable ETL/ELT pipelines, and ensuring data quality and governance. Proficient in translating financial requirements into data solutions while collaborating with investment teams and stakeholders.

Highest-signal resume keywords

• Python Development
• ETL/ELT Pipeline Development
• Data Engineering
• Power BI Solutions
• Google Cloud Platform

ATS Optimization Keywords

Hard Skills

• Data Modeling
• Analytical Data Products
• Transformation Logic
• Data Quality Controls
• Investment Analytics
• Dbt Framework
• BigQuery
• Prefect
• Dagster
• Airflow

Soft Skills

• Collaboration
• Communication
• Problem-Solving

Industry Keywords

• Investment Workflows
• Financial Datasets
• Analytics Engineering
• Data Governance
• Operational Runbooks

Tools & Technologies

• Power BI
• Streamlit
• GitHub
• Docker
• CI/CD