CLOSING DATE:
September 26, 2026
Opportunity
The Economics & Investment Research (E&IR) is AIMCo's in-house macro and investment research function. We exist for one purpose: to help the Chief Investment Officer, senior investment leadership, investment committees, investment teams and our clients make better-informed decisions about how capital is positioned.
Our product is a combination of evidence-based analysis, judgement and the tools that sharpen both.
The role
Reporting to the Chief Economist and Head of Economics & Investment Research, the Director, Quantitative Investment Research is the senior quantitative voice within E&IR. You will own the analytical frameworks behind how AIMCo's E&IR thinks about portfolio construction, risk budgeting, and asset allocation - and you will build the systematic tooling that turns those frameworks into something the CIO and investment committees can act on, cycle after cycle.
This is a hands‑on Director role. You will spend a meaningful share of your time in code and data, and the rest translating results for people who will never open your notebook. You will help mentor a few quantitative analysts, setting the research agenda and the standards it is held to.
The work is deliberately positioned close to the decision. Your analysis will not sit in a research library; it will be in front of the CIO, investment committees, as well as clients and it will be debated.
What this role is - and is not
This advisory mandate is total client portfolio construction, risk, and decision support (not a systematic alpha seat for standalone trading P&L). Candidates who want their work to change how CAD $200 billion is positioned will find it rewarding and purposeful.
What you will do
Portfolio construction and asset allocation research
- Own the advisory quantitative frameworks behind client total portfolio construction across CIO office risk optimization and capital allocation scenario analysis.
- Design and evaluate top‑down portfolio positioning and structure - and translate shifts in the macroeconomic regime into concrete, defensible positioning recommendations.
- Model systematic risk factors across the portfolio, forecast their behaviour, and quantify what holding a given top‑down view actually costs.
- Build and maintain the top‑down frameworks around benchmarking, currency hedging, and liquidity management.
- Develop capital market assumptions and the analytics that connect them to portfolio outcomes, including for private market exposures.
- Work within the real constraints of an asset owner: illiquidity, pacing, funding, and governance timelines - not a frictionless optimizer.
Systematic decision support for the Tactical Asset Allocation Committee
- Build and own the systematic toolkit that supports the TAA Committee: regime and cycle models, valuation and momentum indicators, positioning and flow trackers, and complementary risk dashboards.
- Establish a repeatable cadence - the same evidence, produced the same way, every cycle - so that Committee debate is about judgement rather than about whose numbers are right.
- Frame conclusions probabilistically rather than as point forecasts, and be explicit about where consensus is strong, where it is thin, and where we differ.
- Design scenario narratives, with E&IR and Risk Management colleagues, with the transmission channels made visible: what the shock is, how it propagates, and which exposures it reaches first.
- Backtest and stress‑test proposed tactical tilts, and document both what the evidence supports and what it does not.
- Maintain an honest scorecard of past tactical decisions and model performance, and feed that record back into the process.
Risk analytics and stress testing
- Develop top‑down macro factor risk decomposition, stress testing, scenario, and tail‑risk analytics spanning public and private asset classes.
- In collaboration with Risk Management and Multi‑Asset Portfolio Management colleagues, answer the questions leadership actually asks: how much of our risk is really one bet, what breaks in which regime, and what the marginal dollar of risk buys us.
- Partner with Risk Management as a first‑line analytical counterpart - complementing independent oversight rather than duplicating it.
Research platform, data, and model governance
- Own the E&IR quantitative stack: data pipelines, the research environment, code standards, and reproducibility.
- Set model governance standards - documentation, validation, benchmarking, version control, and periodic review - so that any model informing a decision is defensible to investment committees and Risk.
- Apply AI and large‑language‑model tooling deliberately and with judgement: accelerating research, processing unstructured macro and market information, and building governed interfaces to our own data. We are looking for demonstrated, critical application - not enthusiasm.
- Partner with Risk Management, Global Data and Technology, and the asset class teams to source and inte