Quantitative Analyst

About the Role

The Founding Quantitative Researcher — Credit & Equity Modeling will lead the development of systematic models and research frameworks across credit and equity markets. This is a full-time hybrid role based in the New York City or Boston Metropolitan Areas, with flexibility for partial work from home.

Key Responsibilities

• Designing and testing quantitative strategies.
• Building and validating statistical and mathematical models.
• Translating market, fundamental, and macroeconomic data into robust, explainable signals.
• Collaborating with engineering and product teams to implement models into production.
• Refining factor libraries.
• Enhancing research workflows for institutional clients.
• Authoring systematic research notes.
• Contributing to proprietary rankings.
• Helping shape Echo’s long-term research roadmap as an early foundational team member.

Requirements & Tech Stack

• Proficiency with programming languages commonly used in quantitative finance (e.g., Python, R, or similar).
• Familiarity with data analysis libraries and numerical computing tools.

Qualifications

• Strong foundation in Statistics and Mathematics, including probability, econometrics, and applied linear algebra relevant to financial modeling.
• Experience in Quantitative Investing and Quantitative Research, particularly in credit and equity markets, with a track record of designing and evaluating systematic strategies.
• Advanced Analytical Skills for working with large, complex financial datasets, interpreting factor behavior, and diagnosing model performance.
• Master’s or PhD in a quantitative discipline (e.g., Statistics, Mathematics, Finance, Computer Science, Physics, Economics) or equivalent practical experience.
• Experience building or using factor models, risk models, or signal libraries for institutional research or portfolio construction.
• Ability to communicate technical findings clearly to both quantitative and non-quantitative stakeholders.
• Ability to document research in a reproducible, structured manner.
• Comfort working in an early-stage environment, with the ability to take ownership, iterate quickly, and collaborate across research, product, and engineering teams.