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Quantitative Research Analyst
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 Quantitative Research Analyst plays a hands-on role in both portfolio production and model development, working closely with portfolio managers and the trade operations to ensure research insights are translated into robust, implementable portfolios.
Key Responsibilities
The Quantitative Analyst will:
- Own the day-to-day operation of MAST’s systematic portfolio process
- Produce optimized and implementation-ready portfolios for PM review
- Apply and document investment overrides, translating model output into tradeable portfolios
- Conduct independent research to improve signals, models, and portfolio construction
This role sits at the intersection of research, portfolio management, and implementation, and requires both strong quantitative skills and sound investment judgment.
Portfolio Production & Implementation
- Run and maintain the systematic portfolio construction process
- Generate optimized and implementation portfolios and explain key drivers of allocations
- Partner with PMs to assess model output, apply overrides, and prepare portfolios for execution
- Ensure consistency, accuracy, and robustness of production outputs
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, and sensitivity studies
- Conduct ad hoc quantitative analyses to support investment decisions
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 data sources
- Challenges existing approaches while maintaining discipline and rigor
Communication & Engagement
- Clearly articulates complex ideas and recommendations
- Engages effectively with PMs, peers, and cross-functional partners
Minimum Qualifications
- Bachelor’s degree in a quantitative discipline (e.g., data science, finance, economics, mathematics, statistics, physics); advanced degree preferred
- Strong proficiency in Python; experience with databases and data pipelines preferred
- The ideal candidate would have a solid understanding of financial markets as well as strong quantitative (data science) background. However, a candidate with either skill will be considered if they have a desire to learn the other
- 3–5 years of relevant investment or quantitative research experience preferred
- Progress toward the CFA designation is a plus
Knowledge, Skills, & Abilities Required
The ideal candidate is intellectually curious, outcome-driven, and able to exercise sound judgment in ambiguous situations. They are comfortable working across multiple initiatives and functions in a fast-paced investment environment.
- Strong analytical and quantitative reasoning skills
- Experience with advanced statistical, machine learning or data science methods preferred
- Ability to translate quantitative output into investment-relevant insights
- Comfortable working independently and collaboratively in a fast-paced investment environment
Preferred Skills
- Experience with large, complex financial or macroeconomic datasets
- Familiarity with portfolio analytics, factor models, and back-testing frameworks
- Experience with relational databases (e.g., SQL Server, Postgres)
- Interest in building production-quality research tools and APIs
Compensation Pay Range: This position offers a competitive base salary range of $170,000–$200,000, commensurate with experience and qualifications.
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