Associate, Portfolio Analytics

This Associate, Portfolio Analytics will support the CIO Office in BMO Life Assurance (BMOLA) by delivering high‑quality quantitative analytics across portfolios, liabilities, and balance‑sheet metrics. The position plays an important enabling and influencing function by ensuring that investment conversations are supported by robust, transparent, and timely quantitative analysis. The role develops and maintains analytics, models, and dashboards that help decision‑makers understand portfolio risks, trade‑offs, and balance‑sheet implications.

This is a hands‑on, technical role designed for candidates with strong quantitative and programming skills who want direct exposure to front‑office investment process.

Key Responsibilities:

Portfolio, ALM & Trade Analytics

• Support discount curve construction and maintenance under established methodologies.
• Produce asset‑liability analytics, including duration, convexity, KRDs, and cash‑flow mismatch measures.
• Assist with pre‑trade and post‑trade quantification, calculating impacts on portfolio risk, carry, roll‑down, and surplus sensitivity.
• Run scenario and stress tests (rates, curve shape, spreads) and summarize results for PMs and CIO Office.

Balance Sheet & Risk Analysis

• Calculate surplus sensitivity and risk metrics under different market scenarios.
• Support decomposition of portfolio and surplus risk into rate, spread, and credit components.
• Assist with monitoring concentration, liquidity, and key risk indicators.

Dashboard & Analytics Development

• Build and maintain Python‑based analytics, data pipelines, and calculation engines.
• Develop and update investment and risk dashboards used by CIO Office and PMs.
• Ensure data accuracy, documentation, and reproducibility of analytics.

Collaboration &c Learning

• Work closely with senior analysts, PMs, ALM, and Risk teams.
• Contribute to investment materials and analytics for portfolio reviews and committees.
• Continuously enhance technical and market knowledge.

Required Qualifications:

• SQL, Python/R/SAS, and visualization (e.g., PowerBI) skills are essential.
• Knowledge and experience in capital markets are essential.
• Investment designation preferred.
• Knowledge of investment performance and investment risk strongly preferred.
• Data analytics skills are essential.
• Collaboration & team skills; with a focus on cross-group collaboration.
• Typically, 3+ years of relevant experience and/or certification in related field of study or an equivalent combination of education and experience.
• Bachelor or M.Sc in relevant field preferred.