Quant Developer

Algoedge Technology; Gurugram District; On-site; INR 900,000 - 1,400,000; Full time

Job summary

Algoedge Technology in Gurugram is seeking a Quantitative Developer to design, implement, and maintain systematic trading models in a production environment. You will collaborate with quantitative researchers and trading teams to translate research into reliable, automated workflows.

You will build production-quality code, optimize performance, and scale the technology stack while developing backtesting and simulation tools.

Qualifications

• Strong foundation in Quantitative Analytics and Quantitative Finance, with the ability to translate models into production-ready code.
• Solid academic and practical background in Mathematics and Statistics for modeling, estimation, and risk analysis.
• Understanding of Trading concepts and market microstructure, including how systematic strategies interact with real-world markets.
• Proficiency in programming languages commonly used in quantitative development (e.g., Python, C++, or similar) and experience with data structures and algorithms.
• Experience with numerical computing libraries, data analysis tools, and version control systems.
• Bachelor's or Master's degree in a quantitative field such as Computer Science, Mathematics, Statistics, Physics, Engineering, or related discipline.
• Ability to work in a collaborative, research-driven environment, with strong problem-solving and communication skills.
• Prior experience in systematic trading, portfolio optimization, or high-performance computing is beneficial

Responsibilities

• Design, implement, and maintain production-quality code for systematic trading models.
• Integrate models with execution systems and optimize performance and scalability of the technology stack.
• Analyze market and strategy data, develop tools for backtesting and simulation.
• Translate quantitative research into reliable, automated workflows and contribute to documentation, testing, and continuous improvement of algorithms and infrastructure.

Skills

Quantitative analytics

Quantitative finance

Mathematics

Statistics

Trading concepts

Python

C++

Data structures & algorithms

Numerical computing

Git

Education

Bachelor's or Master's in a quantitative field

Tools

Git

NumPy/SciPy

Job description

This is a full-time, on-site Quantitative Developer role based in Gurugram. The Quantitative Developer will design, implement, and maintain systematic trading and investment models, collaborating closely with quantitative researchers and trading teams. Day-to-day responsibilities include building production-quality code, integrating models with execution systems, optimizing performance, and ensuring robustness and scalability of the technology stack. The role involves analyzing market and strategy data, developing tools for backtesting and simulation, and translating quantitative research into reliable, automated workflows. The Quantitative Developer will also contribute to documentation, testing, and continuous improvement of algorithms, infrastructure, and development practices.

Qualifications

• Strong foundation in Quantitative Analytics and Quantitative Finance, with the ability to translate models into production-ready code.
• Solid academic and practical background in Mathematics and Statistics for modeling, estimation, and risk analysis.
• Understanding of Trading concepts and market microstructure, including how systematic strategies interact with real-world markets.
• Proficiency in programming languages commonly used in quantitative development (e.g., Python, C++, or similar) and experience with data structures and algorithms.
• Experience with numerical computing libraries, data analysis tools, and version control systems.
• Bachelors or Masters degree in a quantitative field such as Computer Science, Mathematics, Statistics, Physics, Engineering, or related discipline.
• Ability to work in a collaborative, research-driven environment, with strong problem-solving and communication skills.
• Prior experience in systematic trading, portfolio optimization, or high-performance computing is beneficial