Summary
The Multi-Asset Solutions Team (MAST) manages a suite of active investment ETFs and delivers standard and customized multi-asset portfolio solutions across approximately $5 billion in AUM. Portfolios span U.S. and international equities, fixed income, and commodities. MAST’s investment process combines systematic quantitative models with a qualitative investment overlay. The Quantitative Research function is central to this process, designing, maintaining, and enhancing the models that translate market and macroeconomic information into portfolio allocations. These include:
- Market regime and business-cycle detection models
- State-space and signal-aggregation frameworks
- Bespoke portfolio optimization engines
- Scenario analysis and Monte Carlo simulations for outcome evaluation
The Senior Quantitative Analyst is a hands-on role spanning research, model development, portfolio construction, and production.
We are looking for a seasoned quantitative professional who has built trading signals, constructed portfolios, and deployed models that run real money. This person will work closely with portfolio managers and trade operations, and is expected to elevate the team’s research capability through deep technical expertise and hard-won market intuition.
Key Responsibilities
- Design, develop, and maintain systematic investment models — including regime detection, business-cycle indicators, signal aggregation frameworks, and multi-asset portfolio optimization engines — that directly drive portfolio allocation decisions across approximately $5B in AUM.
- Bring deep technical expertise in classical quantitative methods — mean-variance and robust optimization, state-space models, Kalman filters, factor models, time-series econometrics, and Monte Carlo simulation. You should understand these tools at a foundational level, not just as library calls.
- Complement that classical foundation with practical machine learning and AI experience — ensemble methods, gradient boosting, reinforcement learning, deep sequence models, LLM-based pipelines, and dimensionality reduction techniques. The team actively integrates AI into its research and production workflows. More importantly, you should know when these approaches add genuine value over simpler methods and when they don’t.
- Bring a proven track record of taking models from research through to live production. We expect candidates at this level to have done this multiple times — designed a model, validated it through rigorous backtesting, deployed it into a production investment process, and maintained it through changing market regimes.
- Conduct independent, self-directed quantitative research to identify new signals, improve existing models, and advance the team’s investment process — formulating hypotheses, sourcing and validating data, running rigorous backtests, and presenting actionable findings to portfolio managers.
- Bridge the gap between quantitative methods and investment judgment. Translate complex model outputs into clear, portfolio-relevant insights for PMs and stakeholders, bringing a cross-asset perspective informed by deep understanding of macro drivers, market regimes, and multi-asset dynamics.
- Raise the intellectual bar of the team. Draw on your experience across markets, methodologies, and past failures to challenge assumptions, introduce new frameworks, and sharpen the team’s research process. We value people who make everyone around them better by sharing hard-won intuition about what works, what doesn’t, and why.
- Write production-quality Python code every day. This is a hands-on role: every member of the team builds and owns their own code.
Research & Model Development
- Research and develop quantitative methods for asset allocation, regime modeling, and portfolio optimization.
- Enhance existing models and analytics through data, methodology, or implementation improvements.
- Perform back-testing, scenario analysis, Monte Carlo simulations and sensitivity studies.
- Conduct quantitative analyses to drive investment decisions.
Portfolio Construction & Design
- Construct and design optimized portfolios and explain key drivers of allocations and design decisions.
- Assess model output, diagnose when a model will/will not work, apply overrides and propose gates/enhancements.
- Review and assess consistency, accuracy and robustness of MAST models and processes.
Key Behavioral Expectations
Drives for Results
- Demonstrates ownership, accountability, and urgency.
- Delivers high-quality output aligned with Harbor’s investment objectives.
Unleashes Innovation
- Actively explores new ideas, techniques, and