Portfolio Researcher (Sr. or VP Level) - Alpha Research Team

BMO U.S.; Toronto; On-site; CAD 80,000 - 175,000; Full time

Benefits offered by this job

Health insurance

tuition reimbursement

accident and life insurance

retirement savings plans

Job summary

BMO Financial Group in Canada seeks a senior researcher to lead the design and development of scalable, production-quality portfolio-construction capabilities using Python and related technologies; ensure outputs are deployable in live investment processes.

You will partner with portfolio managers, develop multi-factor risk models, backtest optimizers, and establish standards for reproducibility and change management while mentoring junior researchers.

Qualifications

• Significant experience in portfolio research, quantitative investing, portfolio management, risk management, or a closely related investment role.
• Demonstrated experience leading complex research programs and influencing portfolio decisions across multiple investment teams or mandates.
• Deep expertise in portfolio construction, optimization, factor analysis, risk modeling, performance attribution, and empirical investment research.
• Strong understanding of how quantitative models operate within live investment processes, including implementation, liquidity, capacity, transaction cost, operational, and governance constraints.
• Fluent proficiency in Python and SQL, with the ability to review analytical methodologies, challenge assumptions, and guide scalable implementation.
• Experience working with financial datasets such as fundamentals, estimates, sentiment, macroeconomic data, factor risk models, security masters, holdings, transactions, and performance data.
• Proven ability to communicate complex research clearly and persuasively to portfolio managers, senior executives, clients, and non-quantitative stakeholders.
• Strong leadership, judgment, and prioritization skills, with a track record of developing talent and delivering high-quality outcomes in a collaborative environment.

Responsibilities

• Lead a portfolio research agenda focused on improving investment outcomes, portfolio robustness, and the consistency of decision-making across strategies and mandates.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• Lead performance attribution, holdings-based diagnostics, and decision-quality studies to distinguish repeatable investment skill from factor, market, or implementation effects.
• Establish robust standards for research design, validation, documentation, reproducibility, model monitoring, and change management; ensure analytical outputs are transparent, auditable, and fit for use in live investment processes.
• Partner with investment, data, technology, product, and distribution teams to develop practical solutions, improve shared capabilities, and communicate portfolio insights to both technical and non-technical stakeholders.
• Lead, coach, and develop quantitative researchers and analysts; set clear priorities, promote constructive challenge, and foster a culture of intellectual curiosity, accountability, and continuous learning.
• Evaluate emerging datasets, quantitative methods, machine learning techniques, and research technologies; prioritize innovations that provide measurable investment or operational value.

Skills

Python

SQL

Portfolio research

Risk modeling

Backtesting

Leadership

Education

Graduate degree in Financial Mathematics / Economics / Engineering / CS

CFA designation (preferred)

Tools

Barra

Axioma

Bloomberg

FactSet

Job description

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

Key Responsibilities

• Lead a portfolio research agenda focused on improving investment outcomes, portfolio robustness, and the consistency of decision-making across strategies and mandates.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• Lead performance attribution, holdings-based diagnostics, and decision-quality studies to distinguish repeatable investment skill from factor, market, or implementation effects.
• Establish robust standards for research design, validation, documentation, reproducibility, model monitoring, and change management; ensure analytical outputs are transparent, auditable, and fit for use in live investment processes.
• Partner with investment, data, technology, product, and distribution teams to develop practical solutions, improve shared capabilities, and communicate portfolio insights to both technical and non-technical stakeholders.
• Lead, coach, and develop quantitative researchers and analysts; set clear priorities, promote constructive challenge, and foster a culture of intellectual curiosity, accountability, and continuous learning.
• Evaluate emerging datasets, quantitative methods, machine learning techniques, and research technologies; prioritize innovations that provide measurable investment or operational value.

Qualifications

• Significant experience in portfolio research, quantitative investing, portfolio management, risk management, or a closely related investment role.
• Demonstrated experience leading complex research programs and influencing portfolio decisions across multiple investment teams or mandates.
• Deep expertise in portfolio construction, optimization, factor analysis, risk modeling, performance attribution, and empirical investment research.
• Strong understanding of how quantitative models operate within live investment processes, including implementation, liquidity, capacity, transaction cost, operational, and governance constraints.
• Fluent proficiency in Python and SQL, with the ability to review analytical methodologies, challenge assumptions, and guide scalable implementation.
• Experience working with financial datasets such as fundamentals, estimates, sentiment, macroeconomic data, factor risk models, security masters, holdings, transactions, and performance data.
• Proven ability to communicate complex research clearly and persuasively to portfolio managers, senior executives, clients, and non-quantitative stakeholders.
• Strong leadership, judgment, and prioritization skills, with a track record of developing talent and delivering high-quality outcomes in a collaborative environment.

Preferred Skills

• Experience supporting a broad range of investment mandates, including mutual funds, ETFs, model portfolios, institutional portfolios, or multi-asset strategies.
• Experience with commercial risk models and investment platforms such as Barra, Axioma, Bloomberg, FactSet, or similar tools.
• Knowledge of machine learning, alternative data, model validation, experiment tracking, and model monitoring within an investment context.
• Experience modernizing research workflows, reducing technical debt, and moving analytical processes from ad hoc research into reliable production environments.
• Familiarity with cloud platforms, workflow orchestration, data lineage, CI/CD practices, and scalable research infrastructure.
• Ability to connect detailed quantitative analysis with broader investment, product, client, and business considerations.

Education

Graduate degree in Financial Mathematics, Statistics, Economics, Engineering, Computer Science, Data Science, or a related quantitative field preferred.

CFA designation strongly preferred; other relevant investment or risk credentials are considered an asset.

Salary

Salary: $80,000.00 - $175,000.00 Pay Type: Salaried The above represents BMO Financial Group’s pay range and type. Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position. BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards.

Benefits

• BMO also offers health insurance
• tuition reimbursement
• accident and life insurance
• retirement savings plans

To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world. As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. To find out more visit us at https://jobs.bmo.com/ca/en.

BMO is a leading bank driven by a single purpose: to Boldly Grow the Good in business and life. Everywhere we do business, we’re focused on building, investing and transforming how we work to drive performance and continue growing the good.

Who we are

We’re proud to be fueling growth and expanding possibilities for individuals, families and businesses. More than 12 million customers count on us for personal and commercial banking, wealth management and investment services. As the 8th largest bank in North America by assets, we provide personal and commercial banking, wealth management and investment services to more than 12 million customers. In Canada, the United States and across the globe, we’ll continue to build, invest and transform to drive performance that serves the good that grows.

Commitment to Inclusion

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process.