Senior Portfolio Analyst

Mackenzie Financial Corporation•Toronto, ON

2d•CA$72,500 - CA$91,000•Hybrid

About The Position

Reporting to the Director, Portfolio Analytics, the Senior Portfolio Analyst will be a key contributor on the team responsible for delivering timely, accurate and scalable portfolio analytics, reporting and data solutions. This role combines core portfolio analytics, reconciliation and data quality responsibilities with a stronger focus on automation, dashboard development, Python and SQL, and AI-enabled ways of working. The successful candidate will help modernize reporting processes, improve control and transparency, and build reusable tools that support business partners across Mackenzie and Investors Group.

Requirements

University degree in business, finance, computer science, data analytics or a related discipline.
2-5 years of relevant experience in portfolio analytics, performance measurement, investment operations, data analytics, reporting automation or a related function.
Strong portfolio accounting knowledge and demonstrated analytical skills.
Practical experience with SQL for data extraction, validation, reconciliation and analysis.
Practical experience with Python or a comparable programming language for automation, data manipulation, reporting or workflow improvement.
Experience building dashboards, management reporting or self-serve analytics using tools such as Power BI, Looker, Tableau or similar platforms.
Strong problem-solving skills with the ability to investigate data discrepancies, identify root causes and recommend scalable solutions.
High attention to detail and the ability to balance accuracy, control, timeliness and responsiveness.
Excellent written and verbal communication skills, including the ability to explain data issues, analytics outputs and technical concepts to business stakeholders.
Self-motivated, flexible, adaptable and able to demonstrate initiative in a changing environment.

Nice To Haves

Working towards or completion of a professional designation such as CFA or CIPM.
Well-versed in performance measurement principles, including time-weighted returns, money-weighted/internal rates of return, chain linking and annualized returns.
Good understanding of derivative instruments, multi-asset portfolios and complex investment products.
Knowledge of GIPS Standards.
Experience with FactSet, Eagle, Bloomberg or similar investment data and analytics platforms.
Experience with SAP HANA, data warehousing, data modelling or enterprise reporting environments.
Experience using approved AI assistants or code-generation tools to accelerate development, analysis, documentation and testing, with appropriate validation and governance.
Experience with VBA, Power Automate, Git or other workflow automation and version control tools.

Responsibilities

Support the production, validation and delivery of investment performance, portfolio characteristics, analytics and related reporting outputs.
Ensure accurate validation of daily accounting, holdings, returns and analytics data; investigate discrepancies, outliers and data breaks; and liaise with internal teams to resolve issues.
Design, build and maintain Python, SQL and other automation scripts to streamline recurring reporting, reconciliation, data extraction, exception monitoring and quality control processes.
Build and enhance dashboards and self-serve reporting solutions that improve visibility into portfolio analytics, data quality, reconciliation status, operational metrics and business trends.
Use approved AI tools to support analysis, documentation, script development, testing and process improvement, while applying appropriate judgement, review and control standards.
Research and resolve complex data, reporting and systems issues, including identification of root causes, procedural weaknesses and opportunities for automation.
Maintain clear process documentation, control evidence, data lineage notes, test cases and change records for automated solutions and recurring deliverables.
Review and verify work completed by others for accuracy, completeness, consistency and adherence to control standards.
Contribute to project work, including requirements gathering, data analysis, user acceptance testing, dashboard prototyping and implementation support.