Job Description

Company Description AlgoEdge is a quantitative research firm that designs and delivers institutional-grade systematic investment strategies across global markets. The firm focuses on data-driven, risk-adjusted performance through multi-asset quantitative approaches tailored for institutional investors. AlgoEdge combines proprietary research, strong quantitative expertise, and advanced execution technology to create scalable investment solutions. Investors can access these strategies via managed accounts or seamless API integrations, enabling flexible deployment. The environment is research-intensive, technology-focused, and geared toward innovation in quantitative finance.
Role Description The Senior Quantitative Researcher/Trader will design, implement, and manage systematic trading strategies across multiple asset classes in global markets. Day-to-day responsibilities include conducting quantitative research, building and testing statistical and mathematical models, analyzing large financial datasets, and optimizing strategies for risk-adjusted performance. The role involves collaborating with engineering and trading teams to implement strategies in production, monitor live performance, and refine algorithms based on empirical evidence. The Senior Quantitative Researcher/Trader will also contribute to portfolio construction, risk management, and execution improvements. This is a full-time, on-site role based in Gurugram.
Qualifications

Candidates should possess strong skills in Statistics and Mathematics, including probability, time-series analysis, and optimization.
Candidates should possess robust Quantitative Research and Quantitative Investing skills, with experience in systematic strategy development and backtesting.
Candidates should possess advanced Analytical Skills, including working with large datasets, deriving insights, and making data-driven decisions.
Proficiency in programming languages commonly used in quant finance (such as Python, R, C++, or Julia) and familiarity with statistical and numerical libraries.
Experience with market microstructure, execution algorithms, and risk management frameworks in equities, futures, or other liquid asset classes.
Graduate or postgraduate degree in a quantitative discipline (e.g., Mathematics, Statistics, Physics, Computer Science, Engineering, Quantitative Finance) or equivalent practical experience.
Ability to work in a collaborative, research-driven environment, communicate complex ideas clearly, and document research and models rigorously.
Prior experience in a quantitative hedge fund, proprietary trading firm, or institutional investment environment is highly beneficial.