Quant Trader

Tradelab Technologies; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Benefits offered by this job

Competitive salary

Performance incentives

Growth opportunities

Job summary

Tradelab Technologies seeks a hands-on Quant Trader with 4–5 years of experience to design, develop, and deploy systematic trading strategies and execution algorithms for equities, derivatives, and F&O products. You will collaborate with research, engineering, and product teams to turn quantitative ideas into production-grade algos on Tradelab’s low-latency platform.

This role requires strong programming skills, a solid statistics/math background, and practical market microstructure

Qualifications

• 4–5 years of experience in quantitative trading or algo execution.
• Strong Python; C++ for low-latency components.
• Backtesting libraries and time-series data handling experience.
• Solid foundation in statistics and numerical methods; ML methods for trading.
• Practical understanding of market microstructure, exchange APIs, and F&O trading.

Responsibilities

• Design and develop systematic trading strategies for equities and derivatives.
• Develop low-latency execution algorithms and smart order routing logic.
• Build and maintain backtesting frameworks, simulation environments, and dashboards.
• Productionize strategies with profiling, latency tuning, and risk controls.
• Ensure compliance with exchange rules; analyze market microstructure and costs.
• Mentor junior quants and support cross-functional knowledge sharing.

Skills

Python programming

Low-latency C++

Backtesting libraries

Time-series data handling

Statistics / numerical methods

Market microstructure

Communication skills

Education

Bachelor’s or Master’s in Mathematics/Statistics/CS/Engineering

Tools

NumPy

Pandas

PyTorch

QuantStats

TA-Lib

FIX protocol

Job description

About Tradelab

Tradelab builds high-performance, cloud-native trading infrastructure (OMS, RMS, low-latency execution, Algo/HFT systems) for brokers and fintechs. We power real-time trading platforms used by leading market participants and are focused on reliability, scale, and advanced algorithmic trading solutions.[tradelab]

About Tradelab

Tradelab builds high-performance, cloud-native trading infrastructure (OMS, RMS, low-latency execution, Algo/HFT systems) for brokers and fintechs. We power real-time trading platforms used by leading market participants and are focused on reliability, scale, and advanced algorithmic trading solutions.[tradelab]

Role overview

We are seeking a hands-on Quant Trader with 4–5 years of experience to design, develop, and deploy systematic trading strategies and execution algorithms for equities, derivatives, and F&O products. You will work closely with research, engineering, and product teams to turn quantitative ideas into production-grade algos on Tradelab’s low-latency platform. This role requires strong programming skills, solid statistics/math background, and practical market microstructure knowledge.

Key responsibilities

• Research, design, backtest, and implement systematic trading strategies for equity and derivatives markets.


• Develop and optimize low-latency execution algorithms and smart order routing logic.


• Build and maintain robust backtesting frameworks, simulation environments, and performance monitoring dashboards.


• Work with engineers to productionize strategies: profiling, latency tuning, risk controls, and integration with OMS/RMS.


• Implement risk management and position-sizing rules; ensure strategies comply with exchange and regulatory constraints.


• Analyze market microstructure, transaction costs, slippage, and market-impact to improve strategy performance.


• Maintain clear documentation of strategy logic, parameters, and trade rationales; participate in code reviews and post-trade analysis.


• Mentor junior quants and support cross-functional knowledge sharing.

Must-have Qualifications

• 4–5 years experience in quantitative trading, electronic trading, or algo execution roles.


• Strong programming skills in Python; experience with C++ for low-latency components.


• Hands-on experience with backtesting libraries, time-series data handling, and vectorized computation (NumPy/Pandas/PyTorch/QuantStats/Py_Vollib/TA-Lib).


• Solid foundation in statistics, probability, and numerical methods; experience with machine learning methods relevant to trading.


• Practical understanding of market microstructure, order types, exchange APIs, and F&O trading mechanics.


• Familiarity with low-latency systems, event-driven architecture, and profiling/tuning techniques.


• Good communication skills and ability to convert research into production-ready code.


• Bachelor’s or Master’s in Mathematics, Statistics, Computer Science, Engineering, Financial Engineering, or related fields.

Preferred

• Experience integrating strategies with OMS/RMS platforms and knowledge of FIX protocol.


• Experience working at a broker, prop desk, or trading technology company.


• Familiarity with Indian exchanges (NSE/BSE/MCX) and their market data feeds.


• Prior publications, open-source contributions, or demonstrated track record of profitable strategies.

What we offer

• Opportunity to build and run production-grade strategies on a high-performance trading platform.


• Collaborative environment with experienced engineers and domain experts.


• Competitive compensation ( Between 40 - 70 LPA) and performance-linked incentives.


• Learning and growth opportunities in algorithmic trading and trading systems engineering.