Overview

Application Deadline: 10/03/2026 Address: 100 King Street West Job Family Group:Customer Solutions Lead the design and development of scalable, production-quality research and portfolio-construction capabilities using Python and related technologies, ensuring research outputs can be reliably deployed and utilized in live investment processes Role Overview We are seeking a highly experienced professional to lead high-impact portfolio research initiatives across BMO Global Asset Management. This role will shape the portfolio research agenda, develop actionable insights for investment teams, and strengthen the integration of alpha research, risk management, portfolio construction, and performance analysis into investment decision-making. The successful candidate will operate as a senior thought partner to portfolio managers and investment leaders, combining deep quantitative expertise, strong investment judgment, and effective leadership. The role will oversee complex research programs, guide and develop scalable investment capabilities, and translate findings into practical improvements across multiple mandates and asset classes. The role combines factor-model expertise, portfolio optimization, risk management and production-quality Python development to manage risk exposures, generate daily trade recommendations and strengthen the portfolio-construction process. Key Responsibilities Portfolio Research Leadership: Lead a portfolio research agenda focused on improving investment outcomes, portfolio robustness, and the consistency of decision-making across strategies and mandates.Investment Insights and Advisory: Serve as a senior research partner to portfolio managers and investment leaders; identify portfolio risks, unintended exposures, concentration concerns, and opportunities to improve risk-adjusted returns.Mandate and Investment Objective Alignment: Develop a fundamental understanding of each portfolio's mandate, investment philosophy, objectives, benchmark, risk tolerance, and regulatory, client, and implementation constraints; ensure portfolio construction processes are appropriately designed and calibrated to deliver the intended outcomes within those parameters.Portfolio Construction, Optimization, and Constraint Calibration: Develop and evaluate portfolio construction frameworks, optimization techniques, constraints, and sizing methodologies; lead robust backtesting to calibrate optimizer constraints across investment signals, market regimes, and mandates, balancing expected return against risk, liquidity, capacity, turnover, concentration, stability, and implementation costs.Risk Budgeting, Position Sizing, and Exposure Management: Establish risk budgets and position-sizing rules that translate alpha conviction, forecast uncertainty, liquidity, and risk capacity into transparent portfolio allocations; advance the use of factor risk models, scenario analysis, stress testing, active and systemic risk, predicted beta, and other diagnostics to identify and manage portfolio exposures effectively.Automated Factor Hedging & Daily Trade Recommendations: Design and implement an automated factor-hedging layer that identifies unintended factor exposures and recommends efficient risk-adjusted hedges while respecting portfolio, liquidity, turnover and transaction-cost constraints.Factor Model Development: Build and apply multi-factor risk models, including factor exposure estimation, factor covariance estimation, idiosyncratic return and risk estimation, and the development of custom factors and covariance methodologies.Performance and Decision Analysis: Lead performance attribution, holdings-based diagnostics, and decision-quality studies to distinguish repeatable investment skill from factor, market, or implementation effects.Research Governance: Establish robust standards for research design, validation, documentation, reproducibility, model monitoring, and change management; ensure analytical outputs are transparent, auditable