Quantitative Research Associate

Quantitative Research Associate Quantitative Research team within QEG conducts deep research to enhance systematic investment platform. Role requires strong research, programming, and finance fundamentals to contribute across the investment lifecycle. Responsibilities Research & Development Researches and develops enhancements to systematic investment processes (alpha generation, signal construction, risk modeling, portfolio optimization, transaction cost modeling, implementation) Builds Python-based tools and workflows to access, clean, and analyze data at scale Integrates machine learning algorithms and large language models into the quantitative investment process Presents research methods, results, and recommendations to senior researchers and leadership; defends conclusions with data analysis and mathematical formulation Partners with portfolio managers and software engineers to deliver end‑to‑end research and production improvements Portfolio Management Contributes to the team’s Python-based research and production codebases Develops proficiency in the team’s codebases, including architecture, data flows, and core investment logic Maintains, debugs, and enhances codebases to support evolving investment and operational requirements Partners with software engineers to ensure production systems are robust, scalable, and transparent, with appropriate monitoring and controls Incorporates market and liquidity insights into portfolio implementation decisions and risk‑aware adjustments Qualifications Required Education Bachelor’s degree in a quantitative field (mathematics, statistics, computer science, engineering, physics, economics, finance) demonstrating ability to conduct original doctoral‑level research Master’s degree may substitute for two years of required experience PhD may substitute for five years of required experience Required Experience Three years of full‑time directly related experience conducting applied quantitative finance research or related experience Three years of full‑time directly related experience with Python or related experience (experience can be concurrent) Preferred Qualifications PhD from an accredited university in a quantitative field or expected completion within the current calendar year Strong interest or experience in financial markets, quantitative investing, and/or fundamental investing Knowledge of Statistics/econometrics, computer science/machine learning, advanced mathematics (linear algebra, calculus, probability) Quantitative software development and proficiency in Python; experience with version control and collaborative development (Git/GitHub) Investment concepts, terminology, styles, models, strategies, and fundamental factors Skill in Searching, evaluating, and synthesizing large datasets; performing complex statistical analyses; preparing concise reports and oral recommendations Planning, organizing, and prioritizing work to manage a high‑volume workload in a fast‑paced, changing environment while delivering accurate, detailed results Communicating complex information clearly and accurately, both verbally and in writing, using judgment and discretion Leveraging large language model tools to improve productivity Ability to Collaborate effectively in an applied quantitative investment research environment Execute quantitative investment research projects from problem definition through implementation, in partnership with senior investment professionals Military Occupational Specialty (MOS) Codes Veterans, Reservists or Guardsmen with experience in the Military Occupational Specialty may meet the minimum qualifications and are encouraged to apply. #J-18808-Ljbffr