Quantitative Research Analyst

Summary

The Multi-Asset Solutions Team (MAST) at Harbor Capital Advisors, Inc. manages active investment ETFs and provides multi-asset portfolio solutions, totaling approximately $5 billion in AUM. These portfolios cover U.S. and international equities, fixed income, and commodities.

MAST's investment process integrates systematic quantitative models with a qualitative investment overlay. The Quantitative Research function is crucial, involving the design, maintenance, and enhancement of models that translate market and macroeconomic data into portfolio allocations. These models include market regime and business-cycle detection, state-space and signal-aggregation frameworks, bespoke portfolio optimization engines, and scenario analysis with Monte Carlo simulations for outcome evaluation.

The Quantitative Research Analyst plays a hands-on role in both portfolio production and model development. This individual works closely with portfolio managers and trade operations to ensure that research insights are effectively translated into robust, implementable portfolios.

Key Responsibilities

The Quantitative Research Analyst will:

• Own the day-to-day operation of MAST’s systematic portfolio process.
• Produce optimized and implementation-ready portfolios for Portfolio Manager review.
• Apply and document investment overrides, translating model output into tradeable portfolios.
• Conduct independent research to improve signals, models, and portfolio construction.

This role bridges research, portfolio management, and implementation, requiring 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 Portfolio Managers 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

Candidates for the Quantitative Research Analyst role are expected to demonstrate:

• Drives for Results: Demonstrates ownership, accountability, and urgency, delivering high-quality output aligned with Harbor’s investment objectives.
• Unleashes Innovation: Actively explores new ideas, techniques, and data sources, challenging existing approaches while maintaining discipline and rigor.
• Communication & Engagement: Clearly articulates complex ideas and recommendations, engaging effectively with Portfolio Managers, 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.
• A solid understanding of financial markets *and* strong quantitative (data science) background is ideal. However, candidates 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.

Key skills/competency

• Quantitative Research
• Python
• Portfolio Optimization
• Asset Allocation
• Data Science
• Financial Modeling
• Statistical Analysis
• Machine Learning
• SQL
• Investment Judgment